Meningkatkan Literasi pada Siswa Siswi SD Negeri Grogol Utara 09 melalui Kegiatan Festival

Abstract: Literacy is a vital aspect of education to ensure students' abilities in comprehending, interpreting, and interacting with various forms of texts. This study aims to evaluate the effectiveness of festival activities as a strategy to enhance students' literacy at SD Negeri Grogol Utara 09. A case study method was utilized to analyze the impact of festival activities on literacy skills, with 50 students from grades IV and V participating. Festival activities included film screenings, poetry readings, and dance performances, with data collection conducted through observation, interviews, and questionnaires before and after the events. Data analysis revealed a significant improvement in students' reading, writing, and speaking skills after engaging in festival activities. Additionally, students' interest in literacy and creative expression also increased positively. These findings affirm that festival activities can serve as an effective means to expand students' literacy beyond conventional curricula, providing a meaningful contribution to holistic education.


PEMANFAATAN FANPAGE FACEEBOOK: PENJAHIT KEBAYA DAN SALON DI DESA SIOPAT SOSOR KABUPATEN SAMOSIR

Abstract: The kebaya sewing service industry and beauty salons are industries that are always in demand by Indonesian people both in cities and in regions. Kebaya is a traditional Indonesian dress. Every religious event and custom almost always uses kebaya cloth. In using kebaya cloth at every event, Indonesian women always make up themselves so that the kebaya cloth used looks more beautiful and beautiful when worn. Therefore, the kebaya cloth sewing industry and beauty salons are one of the service industries that are in great demand by the public in starting a business. The purpose of this community service activity is so that people who start kebaya sewing and beauty salon businesses can reach a wider market by utilizing social media accounts such as Facebook in promoting their business. Facebook social media accounts can be turned into business accounts by adding a fanpage or business page feature. Facebook fanpage is a special page like a blog that contains various kinds of content according to the wishes of its users. The results of this activity are kebaya sewing and beauty salon business actors who have changed their personal Facebook account to a business Facebook account by adding a fan page feature. So that business actors in kebaya sewing and beauty salons can expand their market share through promotions on social media.


A Survey on Optimization Algorithms: Challenges and Future Opportunities

Abstract: This paper conducts a comprehensive exploration of contemporary optimization algorithms, addressing challenges and outlining potential avenues for future research. The survey encompasses a wide spectrum of optimization techniques employed in various domains, ranging from mathematical programming to machine learning and artificial intelligence. It systematically analyses the inherent challenges faced by existing algorithms, including scalability issues, convergence speed, and adaptability to diverse problem spaces. Furthermore, the paper critically examines the impact of optimization algorithms on real-world applications, considering their effectiveness and limitations. The survey identifies emerging trends, such as hybrid approaches and metaheuristic methods that offer promising directions for overcoming current challenges. By synthesizing the state-of-the-art in optimization algorithms, this paper provides a valuable resource for researchers, practitioners, and decision-makers, guiding them towards addressing existing limitations and unlocking new opportunities in the evolving landscape of optimization research.


Pengaruh Media Papan Perkalian Terhadap Hasil Belajar Matematika Siswa Kelas III SD YPK Elim Kota Sorong

Abstract: The purpose of this study was to determine the Influence of Multiplication Board Media on Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Sorong City. This type of research uses Quantitative Research with the research design used is a pre-experimental design with the type One-Group Pretest-posttest. The population is class III A students with a total of 19 students with a sampling technique carried out by nonprobability sampling, namely purporsive sampling. The instruments used are observation sheets and essay tests to measure student learning outcomes, while the results of the analysis of student learning completeness on the average posttest score are 83.84. The reliability test results obtained by Cronbachs Alpha for student responses amounted to 0.852 which means it has a high level of reliability with the normality test of student posttest learning outcomes having a significance level of 0.028 > 0.05. The hypothesis test obtained tcount of 7.001 with df = n – 1 (19-1=18) obtained ttable of 1.729. Based on the results of the analysis of value data, namely tcalculate > ttable (-7.001> 1.729), with a magnitude of significance level of 0.05, the hypothesis is accepted. Thus, it can be concluded that there is an influence of Multiplication Board Media on the Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Malanu in Sorong City.


PENGARUH PENGUASAAN KOSAKATA DAN TATA BAHASA INDONESIA TERHADAP KEMAMPUAN MENULIS EKSPOSISI SISWA KELAS X SMA NEGERI SE KOTA YOGYAKARTA

Abstract: This research aims to: (1) determine whether or not there is an influence of vocabulary mastery on the exposition writing ability of class X SMA Negeri Se-Kota Yogyakarta (2) determine whether or not there is an influence of mastery of Indonesian grammar on the ability to write expositions of class X SMA Negeri Se-Kota Yogyakarta, and (3) determine whether or not there is an influence of mastery of Indonesian vocabulary and grammar on the ability to write expositions of class This research is ex-post facto research. The research subjects were students class X SMA Negeri Se-Kota Yogyakarta. Sampling used a stratified random sampling technique with a total of 345 students taken. Data collection was carried out using ability tests including vocabulary, grammar and expository writing. Data analysis uses product moment correlation analysis techniques and multiple linear regression analysis. The level of error in the analysis results is determined at 5%. The results of the research show that: (1) there is a positive and significant influence of vocabulary mastery on expository writing ability class X student of SMA Negeri se-Kota Yogyakarta with a calculated r value of 0.164, r table of 0.098, relative contribution of 30.29% and effective contribution of 1.82%; (2) there is a positive and significant influence of mastery of Indonesian grammar on the exposition writing ability of class X student SMA Negeri se-Kota Yogyakarta which is indicated by the calculated r value of 0.221, r table of 0.098, relative contribution of 69.71% and effective contribution of 4.18%; (3) there is a positive and significant influence simultaneously on the mastery of Indonesian vocabulary and grammar on the exposition writing ability of class X student SMA Negeri se-Kota Yogyakarta indicated by an F value of 10.950, a regression coefficient (R) of 0.245, and a coefficient of determination (R2) of 0.060. This means that 6% of expository writing ability is influenced by mastery of vocabulary and grammar, while the remaining 94% is influenced by other factors not examined in this research.


Academic Citizenship Behaviour Mediates Between Green Performance Management, Green Training and Development, and Organization Environmental Performance in The Jordanian Government Universities

Abstract: Purpose: This paper aims to examine the academic citizenship behaviour mediating the effect between Green Performance Management, green training and development, and organization environmental performance in Jordanian government universities. Research methodology: The paper contributes to filling this research gap by examining these effects. A sample of 404 employees in the Jordanian Government universities was analysed using contemporary variance-based structural equation modelling (Amos - SEM) software. Results: Results: The findings revealed a favorable correlation between green training and development and two key variables: academic citizenship behavior and organizational environmental performance. Similarly, a positive relationship was observed between green performance management and both academic citizenship behavior and organizational environmental performance. Additionally, a direct positive association emerged between academic citizenship behavior and organizational environmental performance. Moreover, the results unveiled the mediating role of academic citizenship behavior in the relationship between green training and development, as well as green performance management, and organizational environmental performance. Conclusion: This study offers valuable insights for HRM practitioners, emphasizing the significance of Green HRM practices in augmenting organizational environmental performance.


Perancangan UI/UX Aplikasi Kasir Toko Rieska Dengan Metode Design Thinking

Abstract: This research aims to develop a cashier application to improve efficiency and user experience in Rieska stores. By using the UI/UX design method, this application is designed to facilitate transactions and inventory management. The design results show a cashier application that is responsive and easy to learn. Users provided positive feedback, indicating wider adoption in the retail environment. This research highlights the importance of developing cashier applications that focus on user needs in improving efficiency and user experience in retail businesses.


Enhancing Cross Border Crime Investigations through the Application of Mother Tongue

Abstract: This article explores the benefits of using mother tongue languages in cross-border criminal investigations. It highlights the importance of linguistic ability and cultural awareness in detecting international crimes. Mother-tongue languages can improve information accuracy, trust, and communication. However, they can also lead to communication breakdowns, language barriers, and incorrect interpretation of evidence. The article also discusses the challenges of using dominant languages, such as resource requirements, technology's role in multilingual communication, and legal and ethical requirements. The article concludes that embracing linguistic diversity in law enforcement can improve investigations, promote cooperation, and enhance community safety and security.


CREATIVE THINKING PROCESS IN STUDENT‘S SCIENTIFIC WORKS

Abstract: This study aims to explain the process of creative thinking, including analytic, evaluative, applicative, and interpretative students in scientific work. The scientific works studied were in the form of Student Creativity Program, State University of Malang, Indonesia. This research uses a qualitative approach with a content analysis method. This research data in the form of paragraphs, paragraph clusters, and full text. The data source of this research is the scientific work of students. The research data collection technique was carried out by survey and documentation study. The process of data analysis is grouped into three stages, namely data reduction, data presentation, and drawing conclusions. The findings of this study indicate that the process of creative thinking in writing scientific papers can be done with four stages (1) the analytic stage in scientific work looks at the examination of arguments. (2) Evaluative in scientific work looks at the assessment of arguments in accordance with the topic of study. (3) Applicative in the work appears in arguing according to procedure. (4) Interpretations in scientific work appear in the clarification of meaning, so that the meaning conveyed is clear and directed. The findings of this study contribute to an author's understanding of the importance of using creative thinking processes in scientific writing. However, for further research it is recommended to examine the process of creative thinking with different objects.


Gamma Ray Spectroscopy Analysis of Sediments of Coastal Areas in Ennore, Tamil Nadu

Abstract: Objectives: This research focuses on the determination of the natural radionuclides radium, thorium, and potassium in the twenty-six sediment samples collected at the sea, beach, and creek regions of Ennore Port. Methods: The activity concentrations of 226Ra, 232Th, and 40K were determined using gamma ray spectrometry with a high-purity germanium (HPGe) detector. Findings: The average activity concentrations of 226Ra, 232Th, and 40K were in the descending order of 40K (397.58 Bq kg-1) > 232Th (65.83 Bq kg-1) > 226Ra (18.28 Bq kg-1). The estimated average values of radiological parameters such as radium equivalent activity (143.04 Bq kg-1), absorbed dose rate (64.91 nGy h-1), annual effective dose equivalent (0.32 mSv y-1), and external hazard index (0.39) were lower than the respective world average values, reported by United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR, 2000). Moreover, the representative level index and annual gonadal dose equivalent were slightly higher than the world average value. Hence, this research proved that the study area is radiologically safe for humans and the environment. Novelty: A location and sample collection-based novelty is approached to carried out the work. Sea sediments were also collected along with samples from creek and beach regions in order to examine the dispersion of natural radionuclides from land to marine environments. The samples from the beach and creek regions were collected using a Peterson grab sampler. Especially in the sea region, the samples were collected using a Van Veen grab sampler at a depth of 4 m and a distance of 10 m parallel to the shoreline. Keywords: Natural radioactivity, Sediment, Ennore, Gamma ray spectrometry, HPGe detector, Radiological parameters


SIKAP POSITIF MAHASISWA TERHADAP PENGGUNAAN BAHASA INDONESIA DALAM LINGKUNGAN KAMPUS STKIP PGRI PACITAN

Abstract: The purpose of this research was to understand the forms of language attitudes and the factors influencing the language attitudes of students at STKIP PGRI Pacitan towards the Indonesian language. The approach used was descriptive qualitative. Data collection methods in this research included observation, questionnaires, and interviews. The data analysis method used Miles and Huberman's analysis method, which involved data reduction, data presentation, and drawing conclusions. The results of the study showed that the majority of students in the STKIP PGRI Pacitan campus (93%) exhibited loyalty and pride in using the Indonesian language in various aspects, including communication on social media, entertainment, and daily interactions. They were aware of the importance of the Indonesian language in maintaining national unity and considered it attractive and sustainable in the era of globalization. This positive attitude was influenced by factors such as students' knowledge and experiences, a supportive campus environment, emotional aspects as Indonesian citizens, the influence of mass media, and the role of educational institutions. In this increasingly advanced digital era, it is important to continuously enhance understanding, create a supportive environment, and provide resources that promote the use of proper and good Indonesian language to maintain this positive attitude consistently.


Vehicle Speed Detection using Haar Cascade Classifier and Correlation Tracking

Abstract: Objectives: The aim of this study is to develop an efficient and cost-effective solution for predicting vehicle speeds using recorded video data. Methods: The proposed system employs a combination of image processing techniques and computer vision to calibrate cameras for traffic simulation, enabling the extraction of information on average vehicle speeds. It utilizes the Haar Cascade Classifier for object detection, followed by a correlation tracker for vehicle tracking. Speed estimation is achieved through the frame differencing method. The dataset comprises 90 minutes of recorded data from highway cameras, showcasing diverse traffic scenarios with various vehicle types (trucks, trailers, cars, buses, and bikes) at varying speeds. Predicted values are compared with ground truth data obtained from a GPS-equipped car, using Mean Absolute Error (MAE) as the evaluation metric. Findings: The algorithm's performance is evaluated, resulting in an average error rate of 1.72 km/h (2.07%). These findings are compared with state-of-the-art data. Novelty: This study introduces a novel system that combines the Haar Cascade Classifier, correlation tracker, and frame differencing method to track vehicle positions, incorporating bike detection into the analysis, and calculate their moving speeds. A relative analysis underscores the system's performance, emphasizing its effectiveness in real-world applications and demonstrating refinement in accuracy assessment. Keywords: Image processing, Vehicle speed estimation, Haar Cascade Classifier, Correlation tracker, Error rate calculation, Computer vision


Rancang Bangun Sistem Informasi Industri Asphalt Mixing Plant pada PT. Selo Progo Sakti

Abstract: PT. Selo Progo Sakti is a company engaged in the Asphalt Mixing Plant industry. Asphalt Mixing Plant is a production equipment that produces Hotmix in the form of a mixture of asphalt with some aggregate materials used as road pavement materials. This Asphalt Mixing Plant operates for production according to orders from consumers and the character of the production results in the form of hotmix must meet certain temperature criteria for gnats to be spread out on the road media so that it must be avoided so that the product conditions do not occur at low or cold temperatures because it will harden and cannot used for road pavement. Therefore, the accuracy in delivering the product to the location where it will be held will greatly determine the quality of the production after it is held on the road. In addition, product quality is also determined from the job mix or the proportion of the material mixture that has been agreed upon in accordance with the job specifications, so it needs supervision from various parties involved in the implementation of the work. The existence of an information system is a tool for controlling production costs, in this case hotmix products produced from Asphalt Mixing Plant machines are needed to monitor every production process from several departments that have been worked on so that data management can be done quickly and accurately. Therefore, this system was built in order to overcome problems such as calculating the cost of production of hotmix for each product according to jobmix, cost control, inventory control and preparation of financial reports which can be done in one integrated information system. Tools used in making this system is Visual Basic. The application design method uses the ProtoTyping method.


Language Instructors’ and Students’ Perspective on Large Class Size and What is the Best Technique Language Instructors Utilize to Prompt Learning Autonomy in Class

Abstract: In this research, the author identifies the terms of large class size and learning autonomy. The authors exhibit the difference between both terms and explains clearly the idea of both terms. Moreover, the author shows how large class size is related to learning autonomy. The author will then elaborate on how these two terms complete each other. The Author chooses the story of an English teacher who teaches in Nigeria, who is exposed to a large class size confronting different conflicts during this year of teaching. In addition, the author shows how the English teacher overcame these problems and what solutions were chosen that helped to overcome the issue. The Author also exhibits the class size problems and the autonomy in different contexts of other teachers around the world and how they coped with it. He utilized other research papers to show how each teacher dealt with the problem of class size.As a matter of fact, the author shows how a large class size can affect the teaching in class and what solutions are made in order to overcome the large class size complexities. Furthermore, the research also shows the disadvantages of a large class size according to students’ points of view. It also clarifies how students are affected by large class size and how difficult could learning become in class.


Designing A Low Power LeNet Convolutional Neural Network Accelerator for FPGA in IoT Edge Computing

Abstract: With an emphasis on the Xilinx Artix XC7A200T FPGA, in this paper, a Convolutional Neural Network (CNN) tailored explicitly for FPGA deployment is designed and implemented. The method adapts the LeNet-1 model using a hardware description language; this choice is motivated by the model’s minimal size, making it suitable for edge computing devices. With its parameterized module structure, the architecture, known as ‘LeNet,’ offers significant flexibility and adaptability. The design focuses on the modular architecture and diversity of Processing Elements (PEs), crucial for parallel processing in computationally demanding CNN tasks. Convolutional, pooling, and fully connected layers are customized to leverage the FPGA’s capabilities. Multiple filter banks are utilized for effective input processing and feature extraction. The pooling layers are specifically designed to reduce feature dimensionality complexity, thereby improving data fluctuation handling and reducing computational demands. The architecture stands out for its scalability and efficiency, utilizing five different processing units. The parameterization of modules and their successful application on the MNIST dataset, a standard benchmark in Machine Learning for handwritten digit recognition, further illustrate how the architecture may be adapted to different datasets and applications. The implementation of the Xilinx Artix XC7A200T FPGA achieved a power consumption of 1.775 W at 100 MHz, indicating that the design is energy-efficient and suitable for high-demand applications in resource-limited environments. This paper details the module design, parameterization, and integration methodologies employed in the design process of adapting the LeNet-1 model for FPGA.


Features of Scientometric Results of a Russian Scientific Journal: the Case of the Scientific Direction “Economic Sciences” of the Bulletin of Chelyabinsk State University

Abstract: The article presents the results of the use in the academic community of articles of the scientific journal Bulletin of Chelyabinsk State University in the direction of “Economic Sciences”. The study is based on data from the RSCI information system for 2018–2022. The total number of citations for each issue, individual articles, and the H‑index for issues and by year were calculated. The main trends and patterns in citing articles have been identified, including a three-year delay, passion for the topic of digitalization, inattention to articles by young authors and to international topics. The results of the study may be useful to editors of scientific journals for comparing the indicators of their journals with the one studied in this article, as well as for improving editorial policies.


Kajian Sosiolinguistik Penggunaan Bahasa dalam Percakapan Mahasiswa Semester V Prodi Pendidikan Bahasa dan Sastra Indonesia STKIP PGRI Trenggalek

Abstract: The use of language in speech in everyday life has a big influence on the articulation of communication and interaction between humans. This interaction creates a unity that binds various differences. Therefore, linguistic diversity is unique in the field of communication. The important role of communication tools is to support clarity and the functioning of social life. The use of language in educational institutions is greatly influenced by the environment. As a result, the dialects used by Indonesian students are very unique and diverse. In general, this research aims to determine the diversity of languages used by various students in educational institutions and their environments, especially Indonesian Language and Literature students.


Peningkatan Kompetensi Komunikasi Bahasa Inggris Pramuwisata Lokal Desa Tista Melalui Pelatihan Merancang Tour Itinerary

Abstract: The importance of a tour guide competence and professionalism is the rational of this community service program.The focus of this program is to increase the competence of local tour guides in English by being able to design tour itinerary. This activity was done in Tista Village that is located in Kerambitan District, Tabanan Regency, Bali. The purpose of the activity is to help tourism actors especially local tour guides in Tista Village to enhance their English as one of the competency demands. Community Based Research (CBR) approach was implemented that prioritizes community needs and allows space for local wisdom as knowledge and solutions for the community. The service program was carried out using several methods, namely the lecturing method, question and answer method as well as discussion, as well as demonstration and simulation methods. Providing added value for local tour guides, the activities also include designing tour packages and practicing explaining them in English. The application of role play activities creates a more active and attractive learning atmosphere and has succeeded in increasing the participants' self-confidence as local tour guides. Through training activities in the community service program, the participants are able to understand and practice the English language used in explaining tour itinerary and packages.


Penyederhanaan Birokrasi pada Dinas Perpustakaan dan Kearsipan Daerah Provinsi Jawa Barat

Abstract: Simplification in the bureaucracy is one of the focuses of the 5 (five) priority programs of the Onward Indonesia Cabinet under the leadership of President Joko Widodo and Ma'ruf Amin and as a presidential mandate which is an executive order that must be carried out. We must continue to simplify the bureaucracy on a large scale. Investment for job creation must be prioritized. This study aims to determine the simplification of bureaucracy in the Regional Library and Archives Office of West Java Province. The method used in this study is qualitative by using data collection techniques by observing, interviewing and documenting. The results of this study are that the services available at the Regional Library and Archives Service of West Java Province are appropriate and in the alignment of administrative positions to functional positions because the simplification of the bureaucracy has the advantage that services become simpler, agile, fast and less verbose Regional Library and Archives Services West Java Province simplified the bureaucracy on the basis of government policy with the aim of facilitating the delivery of services to the community more quickly.


Pengembangan bisnis jasa “kaluna badminton club” menggunakan business model canvas

Abstract: Kaluna Badminton Club is a service business that provides a platform for young children to teenagers to become talented and accomplished athletes by practicing using the correct basic badminton techniques. The purpose of establishing this business is because there is not yet a single club that accommodates children from young age to adults to become proficient at playing badminton with the correct basic techniques in Imogiri District. This research was conducted to find out how to manage and develop business strategies at the Kaluna Badminton Club using the Business Model Canvas concept. The Business Model Canvas framework is used as a tool to achieve business targets in a detailed and structured manner. By using this study, it becomes easier for business processes to achieve their goals. The research results from this Business Model Canvas identification can provide the right business strategy choices for the Kaluna Badminton Club in each block. The blocks on the Business Model Canvas include customer segments, value propositions, channels, customer relationships, key resources, key activities, key partners, cost structure, revenue streams. Each of these blocks has its own role which is very important for achieving the business model.


CLASSIFICATION OF SMS SPAM WITH N-GRAM AND PEARSON CORRELATION BASED USING MACHINE LEARNING TECHNIQUES

Abstract: The Short Message Service (SMS) has garnered widespread popularity due to its simplicity, reliability, and ubiquitous accessibility.This study aims to enhance the efficacy of SMS classification by refining the classification process itself. Specifically, it strives to streamline the process by diminishing feature dimensions and eliminating inconsequential attributes. The textual data undergoes preprocessing, which involves employing the N-Gram technique for feature representation, followed by meticulous feature selection utilizing Pearson Correlation. The study employs 5 of classification algorithms. Notably, the findings underscore that the optimal outcomes emerge from the fusion of the N-Gram methodology with feature selection through Pearson Correlation. Among these, the Support Vector Machine methodology stands out, exhibiting a remarkable 91.41% enhancement in accuracy without feature selection, a further improvement to 91.96% through N-Gram utilization, and a final performance of 70.80% following the inclusion of weighted correlation. However, it is imperative to acknowledge the limitations inherent in the model's generalizability, primarily stemming from the utilization of a relatively modest dataset. Despite the efficacy of Pearson correlation and N-gram-based feature selection in curbing data dimensionality and enhancing processing efficiency, certain pertinent features may have been overlooked, or the chosen attributes might not be optimally suited for specific classifications.


Course Construction and Practice of Embedded Computing for New Engineering Education

Abstract: Facing the reform and development of the New Engineering Education, the paper combines the Embedded Computing course construction and practice. The course of Embedded Computing is an elective course for postgraduates majoring in Computer Science in Harbin University of technology. Under the guidance of the education direction for Emerging Engineering Education, it must be strengthened the construction and practice of the course. This paper combines the traditional teaching mode with the online teaching mode, the theoretical content driven by problems with DIY practice, and adopts a diversified evaluation system. Through the curriculum reforms, the students' learning enthusiasm has been actively mobilized, and the teaching quality has been significantly improved. This paper can provide reference for reform of talent training in our teaching courses.


Sustainable Food Supply Chains Through Artificial Intelligence – Conceptual visualization using the example of turkeys to promote animal welfare and food quality

Abstract: The concept visualizes a sustainable food supply chain through the use of artificial intelligence, using the example of turkeys to promote animal welfare and food quality. The technology push through artificial intelligence along the food supply chain is identified as a driver. In terms of market pull, it becomes clear that stakeholders are demanding transparency and the avoidance of food waste. The focus is on the parameters of production processes, use of resources and deriving possible positive effects. The target group comprises stakeholders in the food supply chain and includes producers at the processing and production stages, distributors, retailers and consumers.


Peningkatan Keterampilan Berbicara Melalui Metode Time Token Arends Pada Siswa Kelas V SDN 132 Babalohe Kabupaten Bulukumba

Abstract: The aim of this research is to improve speaking skills through the Time token areinds method in class V Indonesian language subjects at SDN 132 Babalohe. The type of research used is pre-experimental research with the aim of. The research design used was a one-shot case study, namely an experimental research carried out to show the strength of measurement and scientific value of a research design and the experimental units in this research were 19 students in class V at SDN 132 Babalohe as a trial class for implementing the use of Time. Arends Token. The data collection technique in this research was carried out using a student interest in learning questionnaire sheet technique (student responses). The research results show that analysis of student interest in learning questionnaire data shows that the ideal score of 92.89% is in the very good category, because it is in the range of 75% - 100%,Keywords: Effectiveness of Bolding Media (Rolling Ball), Short Story Writing Skills


A Hybrid Visionary for Unveiling Human Motion in the Face of Occlusion with Mask R-CNN, RNN, and MHT

Abstract: Addressing the intricate challenges of Human Motion Detection (HMD), this research presents a pioneering hybrid methodology integrating advanced computer vision and deep learning techniques. Focused primarily on mitigating the impact of occlusion in visual data, the proposed approach employs a Mask Region-based Convolutional Neural Network (Mask R-CNN) for precise motion segmentation. The dual challenges of self-occlusion and partial-occlusion are specifically targeted. The three-fold strategy encompasses motion segmentation, object classification, and tracking algorithms to discern and identify human motion accurately. Motion segmentation involves isolating the moving object within video frames, followed by object classification utilizing a Recurrent Neural Network (RNN) to determine the human presence and to tune the parameter of RNN; this work introduced a novel hybrid Whale Optimization Algorithm and Red Deer Algorithm (WOA-RDA), which gives better convergence speed with high accuracy. To tackle the persistence of occlusion, particularly self-occlusion, Multiple Hypothesis Tracking (MHT) is introduced for robustly tracking human gestures. An innovative aspect of the proposed approach lies in the integration of an RNN trained with 2D representations of 3D skeletal motion, enhancing the model’s understanding of complex human movements. The proposed methodology is rigorously evaluated on diverse datasets, incorporating scenarios with and without occlusion. Experimental results underscore the effectiveness of the hybrid approach, showcasing its ability to accurately identify human motion under varying conditions, thereby advancing the field of human motion detection.


Optimized Fuzzy Model in Piecewise Interval for Function Approximation

Abstract: Function approximation is a technique for estimating an unknown underlying function from input-output instances or examples. Researchers have proposed different methods of function approximations, such as the neural network method, the support vector regression method, the reinforced learning method, the clustering method, the neuro-fuzzy method, etc. This paper introduces a novel data-driven function approximation scheme where the input-output data set is first segmented into multiple pieces. A Mamdani-type fuzzy submodel is constructed for each piece or portion, and the membership functions’ parameters for antecedent and consequent are optimally selected through the differential evolution algorithm. The efficacy of the suggested model is verified on three nonlinear functions, viz., a piecewise polynomial function, an exponentially decreasing sinusoidal function, and an exponentially increasing sinusoidal function. A comparative analysis is done based on the simulation results from the proposed model and the results obtained through the two state-of-the-art function approximation techniques, viz., the support vector regression model and the radial basis function network. The simulation results show that the proposed function approximator has satisfactorily approximated the three functions examined here, surpasses the two state-of-the-art techniques in approximating the two sinusoidal functions, and performs the near-best performance for the piecewise polynomial function. The proposed function approximator is expected to be applied as a new state-of-the-art method for function approximation.


Dynamic Indian Sign Language Recognition Based on Enhanced LSTM with Custom Attention Mechanism

Abstract: In this paper, the author developed a system with an enhanced Long-Short-Term Memory (LSTM) model using a custom Attention Mechanism specifically designed for real-time dynamic Indian Sign Language (ISL) recognition. A large custom dataset of 59 signs was employed. For feature extraction, the MediaPipe framework was used. On this dataset, three different models were trained, the Long Short-Term Memory (LSTM) Dense model with Customed Attention, the LSTM-Dense model with a traditional Attention Mechanism, and the LSTM-Dense model without Attention Mechanism. The proposed Long Short-Term Memory (LSTM) dense model with a customed Attention Mechanism (AM) outperformed the other two models. The proposed LSTM-Dense model with a customed Attention Mechanism achieved a maximum accuracy of 96.08% in predicting the sign. When compared with existing Indian Sign Language recognition methods, our proposed model surpassed all others in accuracy, even with a large number of signs. In addition, 5-fold cross-validation of the proposed model confirmed the durability of our results, with a 93% accuracy. The results show that the proposed recognition system can effectively and robustly recognize ISL gestures.


A Comprehensive Stop-Word Compilation for Kannada Language Processing

Abstract: In this work, a vital aspect of Kannada Natural Language Processing (NLP) takes the stage, with the construction of a standardized stop-word list emerging as a pioneering endeavor. This essential list serves as a foundation for improving language comprehension and processing activities. The work offers a rigorous technique that includes data gathering, tokenization, and TF-IDF score computation using the IndicCorp Kannada dataset. The study innovatively pioneers the construction of a stop-word list exclusively designed for the Kannada language, a first in this domain. The findings highlight the significance of these stop words and their prospective applications in diverse NLP endeavors, providing the framework for the upcoming construction of a Kannada-specific text summarizing work. The human refinement procedure ensures precision in stop-word compilation while considering inherent subjectivity and dataset-specific restrictions. Importantly, this study not only gives valuable insights into linguistic characteristics but also pioneers an innovative approach for stop-word generation in Kannada, establishing itself as a pioneering effort in this specific area of research. Furthermore, the study goes beyond its immediate findings by offering methodologies for the automated compilation and validation of stop words, thus laying the groundwork for further research. This foresight adds to the ongoing advancement of Kannada NLP methods.


Analysis of Copy Move Forgery Detection Process by Applying Fuzzy C Means Algorithm Based on Deep Learning in Digital Image Processing

Abstract: The popularity of digital photos has developed due to technological advancements in the digital environment. Image alteration has become more manageable thanks to powerful and user-friendly photo editing software programs. Therefore, there was a prerequisite to detect the forged part of the image efficiently. Hence, this work emphasizes passive forgery recognition on images tampered by the copy move method, better called Copy Move Forgery Detection (CMFD). Copy Move Forgery (CMF) was fundamentally concerned with covering or repeating one area in a picture by pasting certain regions of a similar picture. Initially, the input digital images were preprocessed through a Gaussian filter to blur the picture to decrease noise. After preprocessing, Multi-Kernel Fuzzy C-Means clustering (MKFCM) was performed to divide the images into numerous clusters to extract the features based on distinctive attributes using the SIFT method. Lastly, with the deep learning technique, the forged parts of the images were detected. The experimental analysis demonstrates that the method was efficient and robust in identifying the forged part of the digital picture, and the performance of the proposed strategy was established on numerous forged pictures.


Prediction of Crime Rate in Diverse Environs Using Hybrid Classifier

Abstract: Crime is the fear and terror among the populace worldwide. Crime is an inherent component of the hazards we encounter daily. In recent times, the mass media has extensively covered numerous criminal incidents, including theft, rape and sexual offenses, robbery, murder, and kidnappings. Various works have been produced to understand the factors that lead to an individual committing a criminal act, the potential dangers involved, and strategies to prevent it. The crime computation technique aims to forecast crime rates, enabling police officers to avoid such incidents effectively. Based on this, a novel prediction approach utilizing a hybrid classifier is suggested. An evaluation of the proposed method was conducted using several criteria. The performance of this recently constructed hybrid prediction model is evaluated by comparing it with established models such as Genetic Algorithm, Particle Swarm Optimization, and Firefly Algorithm. Various performance measures, including error rate, sensitivity, specificity, precision, and execution time, are used for the comparison. Based on the results, this hybrid model is the most optimal crime prediction model compared to the other current models. The suggested approach is executed using the JAVA programming language.


Unified Security Paradigm: Bi-Factor Authentication and Hyper Elliptical Curve Cryptography in IoT-Enabled Cloud Data Protection (BFHECC - IoMT)

Abstract: Ensuring robust security for cloud-stored sensitive information and medical data is critical in contemporary technological landscapes. Safeguarding cloud data involves encryption, access controls, and authentication methods like TLS and multi-factor authentication. Yet, vulnerabilities such as breaches or misconfigurations pose ongoing threats, necessitating continual improvements. The proposed (BFHECC-IoMT) solution integrates a two-factor authentication model and “Hyper Elliptical Curve Cryptography,” presenting a formidable security infrastructure for cloud storage. This framework strengthens data encryption using conventional (password or PIN) and hyper elliptical curve-based authentication methods. It fortifies security beyond typical measures, increasing resistance to cryptographic attacks during data transmission or storage. On the other hand, integrating IoMT and cloud security, bolstered by Homomorphic Encryption and Elliptic Curve Cryptography (HECC), establishes a robust security framework for managing sensitive medical information. Addressing the oversight in existing healthcare systems, this integration ensures enhanced data confidentiality and integrity during transmission and storage. Seamlessly uniting IoMT, cloud security, Homomorphic Encryption, and ECC facilitates secure data transfer from IoT devices to cloud systems, ensuring stringent security standards for maintaining confidentiality, integrity, and availability. This comprehensive approach secures patient data transmission and provides privacy during analysis, compliance with healthcare regulations, and the overall secure handling and analysis of health data in the healthcare sector.


Learning Environment and Factors of Academic Performance among BSED Students

Abstract: This research discusses the relationship between the learning environment and academic performance factors in BSED students. Grounded in the concept of environmental complexity, which encompasses both challenging and supportive elements, the study examines the impact of learning environment variations on student engagement in a classroom setting. Its goals aim to benefit key stakeholders, including the Commission on Higher Education, school administrators, instructors, and BSED students. Commission on Higher Education Officials can use the findings to shape program development and instructor training, fostering an environment conducive to academic success. Higher Education Administrators can gain insights for enhancing learning environments to improve academic performance. Instructors, acknowledged as pivotal contributors, are encouraged to acknowledge their role in cultivating positive and engaging classroom atmospheres. BSED students stand to benefit from a more supportive learning environment, positively affecting emotional well-being and, consequently, academic performance. Employing a quantitative research approach with a descriptive-correlational design, the study not only underscores strong agreement on the equity indicator in the learning environment but also highlights the importance of cooperation, investigation, and equity in influencing student engagement. Additionally, the research identifies the School-Related Aspect as a key factor influencing academic performance, aligning with broader literature emphasizing multifaceted contributors to positive educational outcomes. Pearson R analysis confirms a significant relationship between the learning environment and academic performance factors in BSED students, emphasizing the pivotal role of a positive learning environment in optimizing the learning process and contributing to academic success. In conclusion, the study suggests initiatives for creating positive learning environments, urging collaborative efforts involving administrators, instructors, and students to enhance the overall educational experience.


An Exploratory Study on the Conceptual Factors of Local Education Community Sense

Abstract: The purpose of this study is to explore the conceptual factors that constitute the sense of local education community. For the expansion and development of the local education community, it is important for teachers, who are key members, to have perceptions of the local education community. As for the conceptual factors of teachers' sense of local education community, six conceptual factors were extracted through prior research and consultation with experts: locality, sharing, identity, relationship, practicality, and learnability. A total of 50 survey questions were composed based on the extracted factors. Quota sampling was used to select 170 teachers from elementary, middle, and high schools in Busan as the subject of the survey. For data analysis, exploratory factor analysis and internal consistency (Cronbach's α) were calculated using SPSS WIN 28.0, and correlations were verified. It was confirmed that the main conceptual factors that constitute the sense of local education community recognized by teachers include four factors: ‘locality’, ‘learnability’, ‘relationship’, and ‘collaboration’. Perception of the degree of implementation in each of the four areas of the conceptual factors of local education community sense showed that learnability was the highest, followed by locality, collaboration, and relationship. The results of this study can be used as practical data for developing a tool to measure teachers' sense of local education community and at the same time preparing school-local linked educations.


The Relations of Adolescents’ Achievement Goal Orientations to Academic Failure Tolerance : The Moderating Effects of Attributional Style

Abstract: This study aimed to investigate the relations between adolescents’ achievement goal orientations and academic failure tolerance, and moderating effects of attributional style for the relation between them. 490 middle school students participated in the survey of study. A series of hierarchical regression analyses were used to examine the relationships of achievement goal orientations to academic failure tolerance, and the moderating effects of attributional style for those relationships. Mastery-approach orientation and performance-approach orientation showed a statistically significant positive relation to academic failure tolerance. In contrast, mastery-avoidance orientation and performance-avoidance orientation showed a statistically significant negative relations to academic failure tolerance. In the relationships between achievement goal orientations and academic failure tolerance, attributional style showed different moderating effects. For instance, attributional style has no statistically significant moderating effects in the relationship between mastery-approach orientation and academic failure tolerance. Whereas ability attribution showed a statistically significant negative moderating effect in the relationships of mastery-avoidance, performance-approach, performance-avoidance orientation to failure tolerance. In addition, external(powerful others, chance) attribution showed a statistically significant positive moderating effect in the relationships of mastery-avoidance, performance-approach, performance-avoidance orientation to academic failure tolerance.


Development of Android-Based Interactive Mobile Learning with Guided Inquiry Models to Improve Higher Order Thinking Skills on Light Wave Material

Abstract: This research aims to produce Android-based interactive mobile learning with a guided inquiry model of light wave material that is able to improve students' HOTS abilities. This research is a 4D model type research. The research was conducted at MAN 1 Ponorogo, MAN 2 Ponorogo, and SMAN 1 Badegan. The research subjects were 149 class XI MIPA students who gave a pretest-posttest. Student pretest-posttest data were analyzed using 1-way ANOVA to determine the differences in students' HOTS skills in the control and experimental classes. Based on the 1-way ANOVA test, it was found that there were differences in students' HOTS abilities in the two classes. Classes that use Android-based interactive car learning get higher results compared to classes that don't use Android-based interactive car learning.


Influence of Mobile Learning Based on Articulatde Storyline 3 on Colloid Materials on Students' Learning Interest

Abstract: This research aims to measure students' interest in learning through the use of mobile learning based on storyline 3 on colloidal material. The type of research used is experimental research. The subjects in this research were students in class XI MIPA SMA Negeri 1 Seyagen, totaling 17 students. In this research, students' interest was measured using the Pretest-Posttest technique by administering an interest questionnaire. From the results of the analysis, it is known that there was an increase of 4 students who were promoted from high to very high. The pretest and posttest results of learning interest show that learning using articulate storyline-based learning media has increased students' learning interest by 23.40%. The results of the paired t-test stated that the use of articulate storyline-based learning media was effective in increasing students' interest in learning. This research aims to measure students' interest in learning through the use of mobile learning based on storyline 3 on colloidal material. The type of research used is experimental research. The subjects in this research were students in class XI MIPA SMA Negeri 1 Seyagen, totaling 17 students. In this research, students' interest was measured using the Pretest-Posttest technique by administering an interest questionnaire. From the results of the analysis, it is known that there was an increase of 4 students who were promoted from high to very high. The pretest and posttest results of learning interest show that learning using articulate storyline-based learning media has increased students' learning interest by 23.40%. The results of the paired t-test stated that the use of articulate storyline-based learning media was effective in increasing students' interest in learning.


Effectiveness of Character-Based Comic Media on Environmental Conservation Sub-Material Learning Outcomes

Abstract: The utilization of learning media is one of the alternatives to increase knowledge for students, especially biology learning. In addition, student character can be improved through media in which there is character insertion. Thus, an innovative learning media is needed to improve knowledge and character through character-based comics on environmental conservation submaterial. This research method is a quantitative experiment, with a pretest-posttest control group research design. The sample consisted of 28 control class students and 30 experimental class students. The instruments were 20 multiple choice questions and 22 character questionnaire statements. Data analysis techniques include knowledge assessment measured using the Independent samples t-test formula. The results of data analysis showed that the knowledge of experimental class students increased significantly, the learning outcomes in the experimental class showed a higher average of 86.67 while the control class was 74.46, the average difference in learning outcomes between experimental and control classes was evidenced by the independent samples t-test test value of 0.00 <0.05, and student character showed a percentage of 81.44% in the excellent category. It is concluded that character-based comic media on environmental conservation submaterial can help improve cognitive learning outcomes and student character.


The Leitmotif Structure of ‘Signs and Recognition’: Music of <Signs>

Abstract: the God's message.


AN ANALYSIS OF EXPRESSIVE SPEECH ACTS IN ONLINE DISCUSSION THROUGH WHATSAPP GROUP

Abstract: This study aimed to investigate an analysis of students’ expressive speech acts in online discussion through Whatssapp group. The method used was descriptive qualitative research, and the data source contained expressive speech acts between teacher and students in online teaching and learning. The data came from online teaching and learning interactions between teachers and students for Indonesian language in class VIII at SMP Negeri 35 Makassar with total of 246 students consisted of nine classes and a total of 56 students as respondents. The results found that expressive speech acts can be found everywhere, including in learning Indonesia subject through apologizing, tempting, motivating, hoping, praising, gratitude, thanking, congratulation, criticizing forms and functions of teacher and students’ expressive speech acts. It can be concluded that many expressive speech acts are used in the interactions between teachers and students in online discussion. This research can contribute to the interaction between students and teacher regarding the expressive speech acts in online teaching and learning interactions through WhatssApp group discussion.


Organizational commitment as mediating between administrative creativity and job performance among department managers at Al Hussein bin Talal University

Abstract: This study examines the impact of organizational commitment on administrative creativity and job performance among department managers at Al Hussein bin Talal University. Job performance refers to managers' ability to accomplish their job-related duties efficiently and effectively. Administrative creativity refers to managers' ability to generate innovative ideas and solutions. Organizational commitment is loyalty to an organization. Quantitative research will be used in the study. Surveys will be distributed to department managers at Al Hussein bin Talal University to collect data. The study will use validated measures of administrative creativity, organizational commitment, and job performance. To examine the relationships and mediating effects among the variables, statistical analyses will be performed, such as correlation analysis and mediation analysis. This study will impact human resource management and organizational development practices at Al Hussein bin Talal University. The university can improve department manager performance by fostering a culture that encourages innovation and administrative creativity. In addition, understanding organizational commitment can improve employee commitment to the organization.


Machine Learning for Anomaly Detection in Accounting Records: A Comprehensive Study

Abstract: Maintaining the integrity of accounting records is vital for financial transparency, regulatory compliance, and fraud prevention. This study explores the application of Machine Learning (ML) techniques for anomaly detection in accounting records, shedding light on the evolving landscape of financial data analysis. It emphasizes the critical role of accurate accounting records in business operations, financial reporting, and regulatory adherence. Amidst increasing transaction complexity, traditional audit methods face challenges in detecting unnoticed irregularities. A detailed examination of ML methodologies, including clustering, classification, and neural networks, showcases their potential in identifying anomalies within accounting data. The study discusses data preprocessing, feature engineering, model selection, and evaluation criteria essential for robust anomaly detection. Real-world case studies illustrate how ML-driven anomaly detection enhances traditional accounting practices, improving accuracy and efficiency. It underscores ML's proactive role in preventing fraud, errors, and compliance breaches. Ethical and regulatory considerations in ML implementation are addressed, highlighting the importance of transparency, accountability, and responsible AI practices. This study serves as a valuable resource for accounting professionals and regulatory authorities, emphasizing ML's transformative impact on maintaining financial accuracy and regulatory compliance.


How Search Engine Optimization (SEO) Grew from Nascent Stages to AI

Abstract: The journey of search engine optimization (SEO) from its nascent stage to the present day has been remarkable. Emerging alongside the proliferation of search engines, SEO quickly became an indispensable tool for businesses and marketers striving to enhance their online visibility, attract traffic, and improve rankings. However, as search algorithms advanced, SEO professionals encountered a dynamic landscape marked by evolving trends and new obstacles. For this reason, over time, the factors influencing website ranking have undergone a significant expansion, evolving from a limited set to a multifaceted array. Specific components, such as high-quality backlinks, mobile optimization, local SEO strategies, integration with social media platforms, and the optimization of user experience, have emerged as pivotal determinants of SEO success. These elements assume a critical role in achieving elevated rankings and heightened visibility across search engines, thereby shaping the contemporary landscape of SEO practices. More recently, as search engines and SEO evolve in sophistication, Artificial Intelligence (AI) has found relevance in its integration into SEO. This involvement of AI amidst its benefits, also introduced new challenges and ethical dilemmas into the discuss on search engine optimization (SEO). SEO strategies must exhibit adaptability to maintain efficacy in driving visibility, traffic, and revenue. It is crucial to strike a balance between data-driven decision-making and empathetic marketing. Businesses shouldn't rely solely on AI to preserve the human touch in their marketing endeavors. Hence, navigating the ever-changing terrain of SEO requires marketers and SEO experts to remain attuned to emerging trends and adept at adapting strategies to meet evolving challenges. By leveraging the diverse array of factors influencing SEO success, businesses can enhance their online presence and effectively engage with their target audience in the competitive digital landscape. For this reason, ethical considerations, including data privacy and customer trust, mustn't be side-lined in favor of optimization. Prioritizing ethical practices over all else safeguards the integrity of SEO efforts amidst AI integration.


Enhancing Fraud Detection in Financial Statements with Deep Learning: An Audit Perspective

Abstract: Financial fraud persists as a formidable challenge, necessitating continuous audit innovations to uphold financial statement integrity. This study explores the application of Deep Learning (DL) techniques in bolstering fraud detection within financial audits. It emphasizes the pivotal role of audits in preserving trust and transparency in business. Highlighting the evolving nature of financial fraud, the study underscores the need for auditors to adapt to sophisticated schemes. An examination of DL methodologies reveals the potential of neural networks, anomaly detection, and predictive modeling in uncovering hidden fraudulent activities. The discourse encompasses data-driven strategies, model architectures, and tailored feature engineering. Real-world case studies demonstrate how DL-driven fraud detection enhances traditional methods by improving accuracy and reducing false positives. The study stresses the importance of continuous monitoring, proactive risk mitigation, and timely fraud prevention. Additionally, it addresses ethical and regulatory considerations, advocating for transparency and responsible AI practices in auditing. In conclusion, this study serves as a valuable resource for auditors and regulators, highlighting the transformative impact of DL in fortifying fraud detection and preserving financial reporting integrity.


An Indian Society on Hate Talk: the Differences and Lack of Discourse

Abstract: In India, a society and polity with a mix of cultures, ethnicities, languages, religions, castes and other identities in the country, it is crucial we understand the distinction between free speech and hate speech


AI Integration for Three Language Formula: Advancing Viksit Bharat 2047 Mission

Abstract: The National Education Policy (NEP) 2020 emphasizes the Three Language Formula to promote multilingualism and national integration in India. This paper explores the integration of Artificial Intelligence (AI) technologies to effectively implement the Three Language Formula. It discusses the significance of multilingual education, challenges, and proposes AI-driven solutions. Furthermore, it examines how this initiative aligns with the ViksitBharat 2047 mission, envisioning the role of AI in fostering a developed India by 2047. Through case studies and analysis, the paper provides insights into leveraging AI to realize the goals of NEP 2020, contributing to education advancement and national development. This research is crucial for policymakers, educators, and stakeholders aiming to shape India's educational future.


A Probe into the Sense of Efficacy of the Teachers

Abstract: The concept of teachers’ Sense of Efficacy refers to person’s own belief in his or her capacity to perform their behaviors necessary to produce specific performance attainments in the institution. To ascertain the present status of teachers’ Sense of Efficacy of the school teachers of West Bengal, the present study was carried out through the Descriptive Survey Method by administering Teachers’ Sense of Efficacy Scale (TSES) (Tschannen-Moran & Woolfolk Hoy, 2001) on a random sample of 616 school teachers of West Bengal. The results of the study reflected that on an average the teachers of West Bengal were highly scored in all the subscales of Sense of Efficacy and also in Sense of Efficacy (in Totality). It might be concluded that, the teachers may be perform well in their academic activities and teach efficiently to the students that emphasis the good productivity of quality education.


Perceived Health Behaviors and Learning Needs of Patients with Myocardial Infarction

Abstract: Introduction: - Myocardial infarction is one of the foremost cardiovascular disease causes of mortality and morbidity worldwide. The prevention of this disease requires continuous monitoring and rehabilitative management. It can be achieved by the health promotion of patients using effective, planned educational programs and lifestyle modification by the patient. Patients perceived that their learning needs were unmet and that the information provided was too general. Hence, assessing the healthy heart habits performed by the patient and the patient’s preference regarding learning needs is crucial. The descriptive study is intended to identify the perceived health behaviors and learning needs of patients with myocardial infarction for the first time. Methodology: A quantitative descriptive design was used in this present study. The study included 102 newly diagnosed patients with MI carefully chosen by the non-probability convenience selection method. Information was collected using a patient profile (socio-demographic data, clinical data, and clinical parameters), a Modified cardiac health behavior scale (MCHBS), and a Cardiac patient's learning needs inventory (CPLNI). Results: -The present study result showed that subjects with MI for the first time had a high level of perceived learning needs of 164.11 + 22.28, with symptoms management was 27.61 + 3.763, medication information was 23.15 + 3.010, diet information was 23.12 + 3.148 were the areas perceived as high learning need information among the subjects. Only 11 (10.8%) subjects had a high perception of cardiac health behavior, among which were controlling risk habits and was 14.53 + 3.16. Medication adherence was only 6.76 + 1.89, perception of the subjects regarding dietary management was 19.47 + 4.15, and blood pressure control was 5.09 + 2.13 as considered essential in maintaining a healthy heart. Interestingly, the findings show that subjects with the perception of higher learning needs showed a negatively weak correlation with a lesser perception of health behavior, which is not a statistically significant level at p >0.05. The study highlighted that exercise, habits, and RBS had a statistically significant association with perceived health behavior (χ2= 18.52, p <0.001), (χ2=20.133, p =0.013), (χ2=9.067, p=0.037) respectively. Also, the exposure of subjects to mass media (χ2 =15.01, p<0.05), diversional activities practiced (χ2 =19.08, p <0.01), perception about the prognosis (χ2=7.22, p<0.02), habits (χ2= 13.68, p<0.03) level had a statistically significant association with the perceived learning needs. Conclusion: - Patients’ health behaviors practices and learning needs will change according to their perceptions. Determining the learning needs will help to guide the patient to achieve good cardiac health behaviors practice, subsequently reducing the reoccurrence of myocardial infarction.


Perception of M.ed. Student-teachers Towards Internship as a Part of Teacher Training Programme

Abstract: Teaching is an exciting and rewarding activity but like other professions it is demanding as it requires that its practitioners clearly understand what should be done to bring about the most desirable learning in the pupil and be highly proficient in the skills necessary to carry out these tasks. All the teachers training institutions are not only imparting theoretical but also practical knowledge and skill in teaching different subjects to prospective teachers. There are many parts of teacher training programme like Internship, sessional Work, Project work, micro and macro teaching etc. Internship is an integral part of professional preparation that includes practice – teaching and wide variety of field experience under the guidance of a competent or expert supervisor. Internship in M.Ed. is very essential for today’s teacher because it gives proper training to the student-teachers for better understanding of all the students. It builds confidence among the student-teachers. Therefore, the objective of the study is to know the perception of M.Ed. students-teachers towards the internship programme. In the present study, the researcher has used the descriptive method of research. The total sample includes 100 M.Ed. students-teachers from three M.Ed. colleges of Jammu. A Self-constructed questionnaire was prepared to collect the required data. After collecting the data, the frequencies were calculated to analyze the data. The findings of the study revealed positive perception of student-teachers towards internship as a part of professional preparation of teacher. The present study is helpful for educationists, practitioners, students, stakeholders, policy-makers, teachers and parents.


A Study on Growing Popularity of Digital Wallets among Youngsters in Kerala

Abstract: Any economy's lifeblood is seen as being money. Transactions are now simple in the current environment because to the constant advancement of technology, the internet, and mobile phones. Money transfers and other payment methods are offered on the market. The primary component of digitization is mobile wallets. As opposed to using cash, people prefer to make digital payments. People now prefer cashless transactions more than they did in the past due to demonetization and the unanticipated COVID outbreak. Because money notes are handled by many different people, the transmission of pathogens is also possible. Mobile wallets have greatly simplified and improved our way of living. A digital wallet safely and conveniently maintains all of the users' payment information. There is far less need to carry actual wallets as a result. Only the mobile wallet allows a smart phone to be used as a wallet. These wallets allow for the secure addition of money as well as direct bank account integration. India is moving towards a digital future. Digital wallets are a key component of the digitization process. Within this little time frame. Based on diverse observations, several academics from across the world have investigated digital wallets. However, there is no evidence that anyone has looked into how prevalent digital wallets are among young people. Therefore, the goal of the study is to determine how common digital wallets are among young people. In this study, the gender disparity in usage, transaction volume, usage experience, and transaction count in digital wallets is being examined.


Deblurring using Reverse Filtering Techniques: An Experimental Analysis

Abstract: Images are an integral part of life. Blurring an image is a process that makes the image less sharp and distorts the detail of an image. The images got blurred due to atmospheric noise, improper camera setting, and relative motion between the camera and the scene. Deblurring is the process of recovering the sharp image from the blurred image. The types of blurs include Average blur, Motion blur, Defocus blur, Gaussian blur, etc. Mainly deblurring techniques are categorised into blind image deconvolution and nonblind image deconvolution. There exist many deblurring techniques in the literature. Deblurring using reverse filtering is to suppress the effect of the filter using the filter itself as many times as needed but without knowing its internal structure. The filter is regarded as a black box. This paper presents the experimental analysis of existing reverse filtering techniques such as zero order reverse filtering (T-method), Rendition method (R-method), P-method, and TDA (Total Derivative Approximation). The methods considered in the paper are spatial domain methods.


Enhancing Teacher Education: Cultivating the Architects of Tomorrow’s Mind

Abstract: This article underscores the urgent need for a revamp in teacher education programs to better equip educators as architects of future minds. In the face of rapid technological advancements and evolving educational paradigms, educators' roles have become increasingly intricate. The article explores current challenges in teacher education and advocates for trans-formative approaches aligned with the dynamic needs of 21st-century learners. Key themes include integrating technology, fostering critical thinking, and promoting culturally responsive pedagogy. Drawing on research and best practices, the article proposes a comprehensive framework emphasizing experiential learning, interdisciplinary approaches, and continuous professional development. It emphasizes collaboration between academia, institutions, and policymakers to create a supportive ecosystem. The article advocates for innovative teaching methodologies like project-based learning to prepare educators for the evolving educational landscape. By reviewing existing teacher education models, the article aims to offer insights into effective strategies, emphasizing the significance of fostering a growth mindset among educators. Ultimately, it calls for a paradigm shift, positioning educators as architects of tomorrow's minds, ready to shape an empowered generation capable of meeting future challenges.


Cybersecurity in Tanzania: Opportunities and Challenges

Abstract: Tanzania, like many developing nations, is undergoing rapid digitalization. While this brings numerous benefits, it also opens the door to increased cybersecurity threats. This abstract explores the unique landscape of cybersecurity in Tanzania, highlighting both the opportunities in emerging digital technology, government initiatives, increased awareness and collaborative approach. On the other hand it describe the challenges that lie ahead such as cybercrime landscape, limited digital literacy, data privacy concerns, inadequate resources and infrastructures.


Accelerating the process of text data corpora generation by the deterministic method

Abstract: The object of research is the process of generating text data corpora using the CorDeGen method. The problem solved in this study is the insufficient efficiency of generating corpora of text data by the CorDeGen method according to the speed criterion. Based on the analysis of the abstract CorDeGen method – the steps it consists of, the algorithm that implements it – the possibilities of its parallelization have been determined. As a result, two new modified methods of the base CorDeGen method were developed: “naive” parallel and parallel. These methods differ from each other in whether they preserve the order of terms in the generated texts compared to the texts generated by the base method (“naive” parallel does not preserve, parallel does). Using the .NET platform and the C# programming language, the software implementation of both proposed methods was performed in this work; a property-based testing methodology was used to validate both implementations. The results of efficiency testing showed that for corpora of sufficiently large sizes, the use of parallel CorDeGen methods speeds up the generation time by 2 times, compared to the base method. The acceleration effect is explained precisely by the parallelization of the process of generating the next term – its creation, calculation of the number of occurrences of texts, and recording – which takes most of the time in the base method. This means that if it is necessary to generate sufficiently large corpora in a limited time, in practice it is reasonable to use the developed parallel methods of CorDeGen instead of the base one. The choice of a particular parallel method (naive or conventional) for a practical application depends on whether or not the ability to predict the order of terms in the generated texts is important


Development of a natural language chatbot interface for website users

Abstract: Today, there are a variety of technology solutions for creating chatbots, including universal platforms such as Google's Dialogflow, Microsoft's Azure Bot Service, and IBM's Watson Assistant, as well as chatbot builders such as ActiveChat, SendPulse, and BotPress. The disadvantage of the considered platforms and designers is the limitation of the free plan. This study considered the development and integration of an informative chatbot into the department's website in order to create a virtual assistant for potential applicants and applicants. The relevance of the study is due to the modern conditions of admission, limited opportunities to conduct career guidance events in connection with the consequences of the COVID 19 pandemic and the war on the territory of Ukraine. The object of research is a system of informing website users using natural language. A software product has been developed, which is an information system for applicants. The dynamic JavaScript programming language combined with the Node.js code execution environment and the Telegraf library was chosen to create the chatbot. The Heroku cloud platform with an integrated Heroku PostgreSQL database became the server for the operation of the chatbot. The system is implemented using the @BotFather Telegram service, which makes it possible to integrate it into any web resource. The stages of chatbot development are highlighted with examples of information, linguistic, and technical support. An analysis of the compliance of the developed chatbot with regard to the criteria of informativeness, multimodality, emotionality, productivity, and interactivity was carried out. The structure of the information content of the chatbot, which includes a set of modules, has been developed. A test version of the chatbot has been designed, tested, and integrated into the website of the Department of Applied Linguistics, which will continue to be tested and improved in 2023–2024. Practical significance: the structure of information content and the method of developing a chatbot could be used to develop authentic systems for informing applicants in institutions of higher education


Electronic anonymous voting system based on blind digital signature

Abstract: Представлена схема создания системы анонимного дистанционного голосования, в основе которой лежит алгоритм слепой электронной подписи — один из эффективных способов сформировать и подписать бюллетень для голосования. Описан метод построения канала связи для анонимной передачи бюллетеней на сервер и доказана надежность такого метода, а также указан рекомендуемый способ безопасного хранения бюллетеней голосования в виде блокчейн-транзакций. В ходе исследования были изучены возможные угрозы безопасности системы и представлены способы их предотвращения. Таким образом проанализирована надежность представленной системы и продемонстрировано, что система анонимного удаленного голосования не подвержена этим уязвимостям. Nowadays, remote voting systems and applications become very popular, but they have some drawbacks, especially in terms of anonymity. The aim of the paper is to create a scheme for developing a reliable anonymous remote voting system. The methodology for designing such a scheme is based on the algorithm of blind ballots digital signature. This algorithm is one of the effective ways to generate and sign a voting ballot, where its encrypted voting results are transmitted to the ballot server without any information about user. A secret channel protocol was created to anonymously transfer ballots from voters to a server. This article proves the reliability of this method and also presents a recommended method for securely storing ballots as block chain transactions. In addition, possible threats to the security of the system were investigated and analyzed and there were presented possible ways to prevent them. As the result of this work, an effective scheme for creating an anonymous remote voting system with relatively small number of participants was described. Moreover, the reliability of the presented system was analyzed and it was demonstrated that the system of anonymous remote voting is not affected by possible vulnerabilities discovered during the investigation. As a result of the performed research, it was shown that the presented anonymous remote voting scheme is a good alternative to traditional voting and other similar systems.


Web-Based Tourism And Culture Information System Using Google Api At The Blora Regency Tourism And Culture Office

Abstract: With the increasingly rapid development of computer technology, internet media is a very effective means of conveying information. Through the internet, various kinds of information from various fields can be obtained quickly. The internet has become an important part as a forum or promotional medium. With the advantages of the internet, the author tries to provide information about the existence of tourism and culture in Blora so that the people of Blora city in particular and people outside the city of Blora in general know it easily and save time. The design of this system was made through several stages. The supporting software used is Apache, Macromedia Dreamweaver MX and PHP as server side-scripting and the final result of this research is a website that provides information about Tourism and Culture of Blora Regency.


Conceptual Framework of Inclusive Human Resource Management to Support Neurodiversity Employment

Abstract: This study aims to proposed a conceptual framework for inclusive human resource management in supporting neurodiversity employment. As organizations increasingly commit to fostering diversity and inclusion, the integration of neurodiversity into the workforce has emerged as a contemporary trend. This concept seeks to harness the unique talents of neurodivergent individuals, thereby enhancing organizational performance. However, the adoption of neurodiversity also introduces distinctive challenges within organizations’ human resource management practices, an aspect that has received limited attention in the human resource management literature. To address this gap, the study explores institutional forces, human resource management approaches, and perceived inclusion that influence the support for neurodiversity within organizations based on relevant literature. Through this exploration, the authors aim to provide a comprehensive understanding and a practical framework for guiding future research on neurodiversity in the workplace, enriching the discourse on inclusive human resource management and facilitating more informed organizational practices.


Influence of Financial Performance and Environmental Performance on Company Reputation

Abstract: The purpose of this research is to analyze the reciprocal influence between financial performance and environmental performance on corporate reputation. The population used consists of non-financial companies listed on the Indonesia Stock Exchange (BEI) from 2019 to 2022. The sample size is 28 companies each year, selected using purposive sampling. This study utilizes documentary data, including annual reports, the Corporate Image Index (CII) published by Frontier Consulting Group, and the PROPER index published by the Ministry of Environment and Forestry.The results of this research, using simple linear regression analysis, indicate that financial performance has a positive and significant effect on corporate reputation. Corporate reputation has a positive and significant effect on financial performance. Environmental performance has a negative and non-significant effect on corporate reputation, while corporate reputation has a negative and significant effect on environmental performance. Environmental performance has a negative and significant effect on financial performance, and financial performance has a negative and significant effect on environmental performance.The implications of this research, especially for companies, are that it can serve as a basis for strategic decisionmaking. On the other hand, performance is a key aspect in developing reputation for the future.


Video Annomaly Classification Using Convolutional Neural Network

Abstract: The use of surveillance videos is increasingly popular in city monitoring systems. Generally, the analysis process in surveillance videos still relies on conventional methods. This method requires professional personnel to constantly monitor and analyze videos to identify abnormal events. Consequently, the conventional approach is time-consuming, resource-intensive, and costly. Therefore, a system is needed to automatically detect video anomalies, reducing the massive human resource utilization for video monitoring. This research employs deep learning methods to classify anomalies in videos. The video anomaly detection process involves transforming the video into image format by extracting each frame present in the video. Subsequently, a Convolutional Neural Network (CNN) model is utilized to classify anomalous events within the video. Testing results using the CNN architectures DenseNet121 and EfficientNet V2 yielded performance accuracies of 87% and 75%, respectively. The testing results indicate that the DenseNet121 architecture outperforms the EfficientNetV2 architecture in terms of performance.


Animals as Criminal Evidence in the Perspective of Criminal Procedure Law

Abstract: This study aims to determine the conception of living things as evidence in a criminal offense based on existing legal regulations in Indonesia; the method used in this research is a normative method with a statutory approach, and the data used is secondary data, in the form of primary legal materials consisting of Law Number 8 of 1981 concerning Criminal Procedure (KUHAP) and the Draft Criminal Procedure Code (RKUHAP). The results of this study found that living things can be used as evidence if they meet several leading indicators, one of which is that these living things must be directly related to a criminal case; the novelty of this research regards the wetting and comparison of animals as evidence from the perspective of the Criminal Procedure Code and Draft Criminal Procedure Code.Keywords: Animals; Crime; Evidence


The Effect of Emotional Display Rules on Service Employee Burnout: A Focus on the Mediation of Challenge Appraisal and Hindrance Appraisal

Abstract:
Emotional display rules are official and unofficial requirements on how people
 should express their emotions to others in organizations, playing crucial roles
 in emotional management. According to the job demand-resources model,
 emotional display rules can cause job stress and burnout because they are
 job demands. However, in light of the challenge-hindrance job stress model,
 the effect of job demands on burnout may differ according to whether people
 perceive them as challenges or hindrances. The purpose of this study is to
 determine the causal relationship among emotional display rules, challenge
 appraisal, hindrance appraisal, and service worker burnout. In this study, we
 postulate that emotional display rules increase burnout, while challenge and
 hindrance appraisals mediate the display rules-burnout relationship. A total
 of 213 survey responses were collected from frontline workers in the service
 industry, and an analysis of results revealed that emotional display rules are
 positively associated with burnout, while challenge appraisal negatively mediates
 the display rules-burnout relationship. We also found that hindrance appraisal
 did not mediate between emotional display rules and burnout, while perceived
 organizational support and self efficacy did not moderate the relationship
 between emotional display rules and burnout. These results may demonstrate
 the possibility that service worker burnout can be buffered with the perception
 of emotional display rules as challenging rather than hindering job demands.
 In addition, they imply that service workers’ perceptions and mind controls
 are more important than external factors like organizational support in managing
 job demands, such as emotional display rules. This study shows the importance
 of job appraisal in understanding service workers’ stresses and burnout.


Korean EFL Learner Preference for Voice-Based Audio Asynchronous Online Discussion

Abstract: This study explores Korean EFL learner preferences and perceptions of digital composing (DC) with innovative online technology tools during the implementation of emergency remote learning measures. The research compares learner use of text-based DC and voice-based audio asynchronous online discussion (AOD). This paper investigates the following research problem: What digital modes of interactive, online instructional design can serve as appropriate, learner-accepted replacements for offline instruction? One prior finding indicated that Korean undergraduate EFL learners preferred text and audio DC to video modes. To follow up, this paper investigates 57 learners’ preferences and perceptions toward text-based and voice-based DC, and compares the results. The data analysis methods employ paired-samples Tests, and a thematic analysis to identify issues raised in student comments. The results reveal that learners’ levels of user satisfaction with voice-based audio AOD and their ratings of its perceived usefulness confirm that it can be a satisfactory, effective, and preferable task for engaging learners in digitally-mediated four-skills practice. Another finding is that utilizing a voice-based audio module did not significantly alter learners’ course satisfaction when superseding a text-based module. These findings inform pedagogical practice with empirical insights regarding learners’ use of digital technologies, levels of acceptance, and DC preferences.


The Performance Comparison of DBSCAN and K-Means Clustering for MSMEs Grouping based on Asset Value and Turnover

Abstract: Background: This study focuses on the latest knowledge regarding Micro, Small and Medium Enterprises (MSMEs) as a current central issue. These enterprises have shown their significance in providing employment opportunities and contributing to the country’s economy. However, MSMEs face various challenges that must be addressed to optimize their outcomes. Understanding the characteristics of this group was crucial in formulating effective strategies. Objective: This study proposed to cluster or combine micro, small, and medium enterprises (MSMEs) data in a particular area based on asset value and turnover. As a result, this study aimed to gain insights into the MSME landscape in the area and provided valuable information for decision-makers and stakeholders. Methods: This study utilized two methods, namely the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method and the K-Means method. These methods were chosen for their distinct capabilities. DBSCAN was selected for its ability to handle noisy data and identify clusters with diverse forms, while K-Means was chosen for its popularity and ability to group data based on proximity. The study used a dataset containing MSME information, including asset values and turnover, collected from various sources. Results: The outcomes encompassed identifying clusters of MSMEs based on their closeness in the feature space within a specific region. Optimizing the clustering outcomes involved modifying algorithm parameters like epsilon and minimum points for DBSCAN and the number of clusters for K-Means. Furthermore, this study attained a deeper understanding of the arrangement and characteristics of MSME clusters in the region through a comparative analysis of the two methodologies. Conclusion: This study offered perspectives on clustering MSMEs based on asset value and turnover in a specific region. Employing DBSCAN and K-Means methodologies allowed researchers to depict the MSME landscape and grasp the business attributes of these enterprises. These results could aid in decision-making and strategic planning concerning the advancement of the MSME sector in the mentioned area. Future study may investigate supplementary factors and variables to deepen comprehension of MSME clusters and promote regional growth and sustainability. Keywords: Asset Value, Clustering, DBSCAN, K-Means, Turnover


Impact of Audit Committee Effectiveness on Accrual and Real Earnings Management among Jordanian Listed Firms: Conceptual Paper

Abstract: The aim of this study is to conduct a comprehensive literature review on the impact of audit committees' independence, meeting frequency, and financial expertise on earnings management (both accrual and real). This review will act as a guide for upcoming empirical research. Many countries, when drafting corporate governance legislation, have focused on improving the characteristics of audit committees to deter unethical behaviour by management. Jordan is among the countries that have included provisions in the Corporate Governance Code for listed service and industrial sector companies that emphasise the characteristics of audit committees and their directors. The provisions were implemented in 2009 and revised in 2017. The current study suggests that researchers should choose a study sample from the years 2014 to 2019 to achieve different goals. First, leaving out years after corporate governance started in 2009 lets us check claims that the quality of corporate governance mechanisms improves over time. This is because the years proposed to be left out (2009–2013) are long enough for listed companies to get used to corporate governance. Second, a comparison can be conducted on the quality of corporate governance mechanisms before and after recent reforms. Empirical studies are likely to provide feedback to both legislators and regulators as to whether governance mechanisms are working as intended.


Multiuser-Based Fertilizer Supply Information System In East Plongkowati Kud, Grobgan District

Abstract: KUD Plongkowati Timur is located at Jalan Godong-Karangrayung, Grobogan Regency, which apart from operating in the savings and loan business unit, is also a distributor of fertilizer products produced by PT. Petrokima Gresik and PT. Pupuk Sriwidjaja Palembang. In running the fertilizer distributor business unit at KUD Plongkowati Timur, the process of recording purchase and sales transactions is not carried out using an integrated system in the database, all data is still recorded conventionally by the administration section, while the administration section's computer functions to create reports which are copied from notes provided by cashier so that data security is not guaranteed because the database is not yet integrated. Based on the problems that exist in the East Plongkowati KUD, the author would like to propose a design for a Fertilizer Inventory application system to be taken into consideration in helping speed up the process of recording purchase and sales transactions and can provide the information needed by the East Plongkowati KUD, Grobogan Regency in the form of purchase reports, sales reports, reports. suppliers, customer reports. So the design of the fertilizer inventory information system uses the Microsoft Visual Basic 6.0 programming language with a database from Microsoft Access 2007 and the design of reports from Crystal Report 7. It is hoped that making this application can be one of the efforts that can be made to overcome problems that often occur so that it can increase work effectiveness which of course will have an impact on improving the quality of service to customers.