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Sudah terakreditasi SINTA 2. Editorial Office of Bulletin of Social Informatics Theory and Application Association for Scientific Computing and Electrical, Engineering (ASCEE)-Indonesia Section Jln. Supriyadi, Kel. Surodakan, Kec. Trenggalek, Kota Trenggalek, Propinsi Jawa Timur, 66316 Indonesia Email: businta.2017@gmail.com
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Bulletin of Social Informatics Theory and Application
Published by Association for Scientific Computing, Electronics, and Engineering
ISSN : 26140047     EISSN : 26140047     DOI : https://doi.org/10.31763/businta.v6i2.601
Core Subject : Science, Social,
Computer Science & IT Social Sciences
Bulletin of Social Informatics Theory and Application (ISSN 2614-0047) is an interdisciplinary scientific journal for researchers from Computer Science, Informatics, Social Sciences, and Management Sciences to share ideas and opinions, and present original research work on studying the interplay between socially-centric platforms and social phenomena. Bulletin of Social Informatics Theory and Application is the first Asia-Pacific journal in social informatics. The journal aims to create a better understanding of novel and unique socially-centric platforms not just as a technology, but also as a set of social phenomena and to provide a media to help scholars from the two disciplines define common research objectives and explore methodologies. Bulletin of Social Informatics Theory and Application offers an opportunity for the dissemination of knowledge between the two communities by publishing of original research papers and experience-based case studies in computer science, sociology, psychology, political science, public health, media & communication studies, economics, linguistics, artificial intelligence, social network analysis, and other disciplines that can shed light on the open questions in the growing field of computational social science. To that end, we are inviting interdisciplinary papers, on applying information technology in the study of social phenomena, on applying social concepts in the design of information systems, on applying methods from the social sciences in the study of social computing and information systems, on applying computational algorithms to facilitate the study of social systems and human social dynamics, and on designing information and communication technologies that consider social context.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 132 Documents
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Effects of using problem-solving guide and explanatory support in program visualization tool on reducing students’ misconceptions in learning data structure concepts Mtaho, Adam B
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.649

Abstract

The tendency of novice programmers to hold misconceptions when learning data structures is one of the challenges that novice programmers face in computer science education. Holding misconceptions can result in students’ demotivation and high failure rates in learning the subject. This article presents the findings of an experimental study that was conducted to determine whether using the CeliotM Program visualization tool could help students learn CS 122 (data structures) at the College of Informatics and Virtual Education of the University of Dodoma with fewer misconceptions. The design chosen was a single factor between the experiment designs, with the number of errors committed by the students when writing programs as a dependent variable. The experimental group received instruction using the teaching technique employed by CeliotM, while the control group received instruction using the conventional lecture method. Results show that the use of CeliotM significantly reduced students misconceptions compared to the conventional lecture method. The study's important findings suggest that employing the CeliotM framework can help students understand data structures more effectively by minimizing their misconceptions and hence enhance their programming competencies.
Gamification development in virtual tour Cau Belayu tourism Village Sarja, Ni Luh Ayu Kartika Yuniastari; Sarja, Ni Ketut Pradani Gayatri; Widana, I Putu Krisna Arta
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.650

Abstract

The use of digital marketing is not only specifically for business processes but can also be utilized in the tourism sector. Tourist information, especially tourist villages, can be easily searched via the internet and social media. There is no need to use conventional promotional media, print brochures or advertisements in the mass media, which will cost a lot, especially for tourism village managers. Virtual tour is an example of digital promotional media that is currently developing because it can display real tourist destinations without having to come to the location in person. However, virtual tours only display static images or videos and do not interact with users or tourists other than information, this causes the virtual tour to not have a significant effect on tourist interest to visit in person. There is a need for further development of virtual tours to make it more attractive to tourists to visit, one way is by combining it with other technologies, namely gamification. This research develops a gamification application on a virtual tour for Cau Belayu Tabanan Tourism Village. By applying gamification to the virtual tourist village tour, it is hoped that tourists will be able to experience a more enjoyable and significant impact on tourist interest in visiting the Cau Belayu Tabanan tourist village directly. The research method used refers to the MDLC (Multimedia Development Life Cycle). The research method consists of the stages of concept, design, material collecting, assembly, testing and distribution. The results of this study are in the form of a gamification application in the virtual tour of the Cau Belayu Tabanan Tourism Village which has the main features, namely games, gamescores and game finishes.
Automatic detection and counting of fisheries using fish images Tall, Marc Momar; Ngom, Ibrahima; Sadio, Ousmane; Coulibaly, Adama; Diagne, Ibrahima; Ndiaye, Moustapha
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.655

Abstract

In Senegal, stock recovery and fish classification are based on manual data collection, and the fish caught by the fishery are not often declared. What's more, data collection suffers from a lack of tools for monitoring and counting fish caught at fishing docks. Researchers have carried out studies on the fishery in Senegal, but data collection is almost non-existent. Moreover, there is no local fisheries database or automatic detection and counting algorithm. In this paper, a semantic segmentation algorithm is proposed using intelligent systems for the collection of fishery catches, for the formation of the local database. The data are collected by taking images of fish at the Soumbédioune fishing wharf in Senegal, and are completed with the Fishbase database. They were applied to the algorithm and resulted in a segmented dataset with masks. This constitutes our local database. The database is used with YOLO v8. The latter is very important for detecting images with bounding boxes in order to train the model. The results obtained are very promising for the proposed automatic poison detection and counting model. For example, the recall-confidence scores translate into bounding box performance with scores ranging from 0.01 to 0.75, confirming the performance of this model with bounding boxes
Existence uniqueness and stability for certain operators of nonlinear system of differential equations Abdullah , Dawoud .S; Rafeeq, Ava; Butris , Raad N.
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.656

Abstract

This research contributes to the understanding of nonlinear systems of differential equations with operators, specifically in the context of generalizing Volterra and Fredholm integral equations. The use of the Picard approximation method, Banach fixed point theorem, and stability analysis further enhances the analysis of the solutions. The examples provided help to solidify the theoretical findings and highlight their applicability.
AI chatbot-based learning: alleviating students' anxiety in english writing classroom Hawanti, Santhy; Zubaydulloevna, Khudoiberdieva Munisa
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.659

Abstract

In the ever-evolving landscape of education, integrating innovative technologies can enhance the learning experience for students. ChatGPT, a cutting-edge language processing tool developed by OpenAI, offers exciting possibilities for teaching writing. This advanced AI model can be a powerful asset in the classroom, providing students with valuable resources and support as they develop their writing skills. Seventy-three college students participated in the quasi-experiment. The findings demonstrate that AI chatbot-based instruction reduces students' anxiety about learning English writing. AI chatbots offer instant feedback, allowing students to correct errors immediately. This quick feedback loop can prevent students from ruminating over their mistakes, thus reducing anxiety. With AI chatbot, students can learn at their own pace. They can take time to understand concepts, practice writing, and receive feedback without feeling rushed. This flexibility can alleviate the pressure of strict deadlines in traditional classroom settings. The findings imply teachers to implement chatbot-based learning in the classroom.
Educational technology using multimedia in science learning: A systematic review Riza, Lala Septem; Hasanah , Lilik Nur; Putri , Ananda Hafizhah; Budiman, Budiman; Safitri, Fibriyana; Putri , Liandha Arieska; Hayati , Nurlaila; Solihah, Putri Amelia; Samah, Khyrina Airin Fariza Abu
Bulletin of Social Informatics Theory and Application Vol. 7 No. 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i2.661

Abstract

This systematic review aims to provide a systematic review of the scientific published studies that examined different multimedia tools in the science teaching and learning process to identify the existing multimedia-based tools and understand their usage, application areas, and impacts on the education system. There are 60 articles extracted from the Scopus database from 2012 to 2022. This review generates six averments about the current study; (1) The most numerous multimedia components are text components; (2) the learning process and application of the use of multimedia in science education can be applied at various levels of education; (3) The majority of the study was conducted in the United States; (4) the current use of technology that is most widely used is the use of power points; (5) the role of technology in the learning process as learning tools, teaching tools, assessment, and evaluation; and (6) the most science content conducted in multimedia research is chemistry.
A comparative study of artificial intelligence in education psychology: the cases of Indonesia and Thailand Utina, Sitriah Salim; Chusniyah, Tutut; Inseachiangmai, Jittakorn; Zahra, Gebi Angelina; Pambudi, Kukuh Setyo
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.663

Abstract

Various applications of artificial intelligence (AI) are currently being developed to enhance and transform the educational experience. However, things like culture, society, and ethics may have an impact on how artificial intelligence is implemented in classrooms all around the world. This study aims to analyze the existing use of AI in education in two Southeast Asian nations, namely Indonesia and Thailand, and to compare those two environments in terms of their potential. Specifically, the research will focus on Indonesia. We gathered papers, publications, and websites from both countries in order to perform an in-depth analysis as part of a comprehensive literature study that we carried out. The ethical and social repercussions of using AI in education, the best practices and suggestions for using AI in education, the possibilities and problems presented by using AI in education, and the preparedness and obstructions presented by using AI in education. Our study demonstrates that there are parallels and variances between the perceptions and experiences of educators and students from the two nations about the use of AI in educational settings, and it also makes recommendations for future research and practice
Comparative Analysis of Application Layer Protocols in EV Charging Stations: Evaluating HTTP, MQTT, and Websocket Performance Metrics Argeshwara, Dityo Kreshna; Hadi, Mokh. Sholihul; Sendari, Siti; Irvan, Mhd
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.664

Abstract

In the burgeoning domain of electric vehicle (EV) technology, the advancement of supportive ecosystems plays a pivotal role. There is a marked global uptrend in the adoption of EVs, necessitating a robust network of EV charging stations. Integral to these stations is the infrastructure and the accompanying systems that govern their operation. With increased utilization, the exigency for expeditious service at these charging points escalates. This study undertakes a comparative analysis of three distinct data communication protocols at the application layer, specifically within the context of EV charging stations. The protocols scrutinized include Hypertext Transfer Protocol (HTTP), Message Queuing Telemetry Transport (MQTT), and Websocket. The benchmark for data transmission in this investigation is the delivery of energy information, adhering to the Open Charge Point Protocol (OCPP), a legally standardized open protocol. The data format employed is JavaScript Object Notation (JSON). Data transmission utilizing the three aforementioned protocols was intercepted and analyzed using Wireshark, a network protocol analyzer. Parameters such as latency (delay), jitter (variability of latency), and throughput (successful data delivery over a communication channel) were meticulously examined and subsequently represented graphically to enhance the interpretability of the network protocol performance. The findings reveal distinct transmission characteristics for each protocol, despite identical data payloads. HTTP exhibited the superior throughput, peaking at 31,621 bits per second (bps) during real-time data transmission. Conversely, MQTT demonstrated the most favorable latency and jitter metrics, both for real-time and periodic data dispatches. Websocket, however, registered the lowest throughput in real-time transmission, at 4,941 bps. These divergences underscore the importance of protocol selection based on specific performance criteria within EV charging station ecosystems.
Predicting financial distress of property and real estate companies using optimized support vector machine - particle swarm optimization (SVM-PSO) Ayuni, Ni Wayan Dewinta; Lasmini, Ni Nengah; Dewi, Kadek Cahya
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.667

Abstract

Financial distress is a critical phenomenon in a company that has significant implications for the business itself, employees, investors, and creditors, and can also impact the economy of a country. Predicting the financial distress of a company, including property and real estate companies, becomes one of the crucial things to be studied. The Support Vector Machine (SVM) is said to be the most effective model for prediction and classification among other machine learning methods. However, it is difficult to determine the parameters of the SVM model. Thus, the SVM model's parameters must be improved for higher accuracy results. This research aims to increase the accuracy of the SVM model in predicting the financial distress of property and real estate companies. The optimization method used is Particle Swarm Optimization (PSO). PSO is one of the most well-known techniques for enhancing SVM parameters. The PSO approach takes its cues from how a group of insects or birds interacts to maintain life. Initialized in a D-dimensional search space, the PSO algorithm uses a population of random particles that are considered as points. Each particle modifies its direction using the best experience it discovers (pbest) and the best experience discovered by all other members (gbest) to arrive at the ideal outcome. As a result, throughout the search process, particles will move through multidimensional space to more advantageous locations. The result of this research showed that the SVM model has the highest accuracy at 80.47% while when the PSO method was implemented in the SVM model, the accuracy increased into 83.16%. It can be concluded that the PSO method successfully optimized the parameters and increased the accuracy of SVM model in predicting the financial distress of property and real estate companies listed in Indonesian Stock Exchange.
Monitoring and controlling humidity and pH use of LoRa in IoT-Based hydroponic planting Usman, Usman; Achmad, Andani; Yuyun, Yuyun; Satra, Ramdan; Tribuana, Dhimas; Konate, Siaka
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.672

Abstract

Indonesia, a tropical country with a growing population, has significant potential for food production but faces challenges in meeting this demand. Factors such as generation change, industrialization, and food production monopolies, as well as climate change, food security measures, and a lack of technological progress, affect productivity. Governments need to address these problems by implementing policies such as cost efficiency, supply chain management, minimum labour consumption, and effective food distribution. Food security is vital to the health and well-being of the population, and food is a vital food source to consume. Vegetables, a popular food source, are vital for health and growth. Salad, a plant used for food production, is beneficial to food production and is the main food in the modern market. Technologically speaking, food security is vital to the health and well-being of the population. Governments should focus on improving food security and ensuring that food is accessible to all. The proposed system consists of five sensors: the DHT11 sensor, the TDS meter, the humidity sensor (DS18B20), the water height sensor, and the pH meter. Data from the sensor will be stored in a cloud database via the LoRa communication network, allowing users to access data through Android applications.

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