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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 9 Documents
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Search results for , issue "Vol. 6 No. 2 (2022)" : 9 Documents clear
Impact of Intense Social Media Usage on Sleeping Pattern Ilham, Nadifah Adya; Mahisha Mutharrif Laila; Muhammad Aditia Syauqi; Mohammad Ardy Audya Armadhana; Anusua Ghosh
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.395

Abstract

The sleeping pattern refers to our habit of resting our bodies after a day's activities. This involves the number of hours spent sleeping and the overall wellbeing of the body when performing everyday tasks. When we don't get enough sleep, it immediately affects our health. This unhealthy sleep pattern is caused by several things, one of which is the intense usage of social media. The use of Social Media can affect health, both physically and psychologically. This research relies on systematic literatur review (SLR) method obtained from databases, namely Google Scholar from many countries in the world, and data about digital 2021 global overview report from Hootsuite & We Are Social. Of the 55 studies obtained, 41 studies stated that Insufficient sleep was found to be linked to social media use. daytime sleepiness, insomnia, or sleep patterns. According to the research, excessive usage of social media is related to sleep problems or disruptions. The usage of social media will have a beneficial impact, since it will make daily tasks easier. However, unrestricted use of social media can have a detrimental effect on sleep habits.
The Readiness Analysis of Smart School Implementation Using Technology Readiness Index to Support Smart City Implementation M. Khairul Anam; Indra Prayogo; Susandri; Yoyon Efendi; Erlin; nurjayadi
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.507

Abstract

Smart Schools have been widely applied in several schools within the scope of education and services as they are being encouraged to support Smart City. Smart Schools is a school concept utilizing information technology used in the teaching and learning process in the class and school administration. One of the schools in Pekanbaru City that will implement intelligent schools in Junior High School 17 Pekanbaru. Building smart schools themselves is adequate infrastructure such as servers, labor, and integrated systems and the readiness of schools and students to implement Smart Schools in the future. Therefore, to determine the readiness level of prospective users of the Smart Schools concept, the technology readiness index (TRI) method with four personality variables; optimism, innovativeness, discomfort, and insecurity. The purpose of this research was to find out the readiness index of prospective users in the implementation of Smart Schools and see what factors need to be improved from the readiness of prospective users. This research was expected to help Junior High School 17 prepare schools to become Smart Schools to support smart city implementation in Pekanbaru
Concerns for Digital Privacy in Business and Management: An overview and Future Discourses Recommendation Linando, Jaya Addin; Herwanto, Guntur Budi
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.508

Abstract

This paper aims to highlight the developing awareness of concern for digital privacy from business and management viewpoint. The authors compile data privacy literature in management field and visualize the literature into 4 main clusters of concerns. The 4 main cluster of concerns in data privacy discourse on management field are: internet; roles-trust-security; locations; and consumer privacy. This paper contributes on the development of research and discourse in data privacy and management domain. Besides delivering the overviews of the digital privacy concerns in business and management fields, the paper also places suggestions for future researchers.
Social Network Analysis of The Development of The Halal Industry In Indonesia Apriantoro, Muhamad Subhi; Adelia Eka Nuraini; Hudaifah
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.553

Abstract

This study aims to look at the public sentiment represented by Twitter users regarding the halal industry. Data was taken using Drone Emprit Academic, a big data method that captures and analyzes conversations on social media, especially on Twitter, developed by Media Kernels Indonesia, which is also installed on the Information System Agency of the Islamic University of Indonesia. The research method uses a social network analysis approach to analyze data on social media conversations. The data was obtained after observing for 30 days from trending Twitter topics. The data is processed by the Social Network Analysis (SNA) system, which can be interpreted as a description of the interactions and relationships that always occur between one individual and another in an organization or work environment and the company. We found that the halal industry in Indonesia is growing more rapidly with the existence of social networks. A large number of conversations among Twitter users in Indonesia shows this.
A Review of Sentiment Analysis Approaches for Quality Assurance in Teaching and Learning (RETRACTED) Oghu, Emughedi; Ogbuju, Emeka; Abiodun , Taiwo; Oladipo, Francisca
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.581

Abstract

The education industry considers quality to be a crucial factor in its development. Nevertheless, the quality of many institutions is far from perfect, as there is a high rate of systemic failure and low performance among students. Consequently, the application of digital computing plays an increasingly important role in assuring the overall quality of an educational institution. However, the literature lacks a reasonable number of systematic reviews that classify research that applied natural language processing and machine learning solutions for students’ sentiment analysis and quality assurance feedback. Thus, this paper presents a systematic literature review that structure available published papers between 2014 and 2023 in a high-impact journal-indexed database. The work extracted 59 relevant papers from the 3392 initially found using exclusion and inclusion criteria. The result identified five (5) prevalent techniques that are majorly researched for sentiment analysis in education and the prevalent supervised machine learning algorithms, lexicon-based approaches, and evaluation metrics in assessing feedback in the education domain.
Deep learning in education: a bibliometric analysis Wibawa, Aji Prasetya; Dwiyanto, Felix Andika; Utama , Agung Bella Putra
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.596

Abstract

This study investigates the application and development of deep learning in educational settings. Based on the statistics of scientific papers, analysis done using bibliometrics demonstrates the rise of deep learning in educational settings. Deep learning is having a transformative effect on all aspects of education and learning, as well as research. These findings could pave the way for more investigation into deep learning, particularly in education. According to the bibliometric results, the Netherlands, China, the United States of America, India, and Norway are the five countries that have contributed the most to deep learning in education. Norway came in fifth place. In addition, some of the possible directions that research could go in the future concerning deep learning in education include online, machine, blended, remote, informal, and deep reinforcement learning.
Web-Based System for Medicinal Plants Identification Using Convolutional Neural Network Latumakulita, Luther; Mandagi, Franklin; Paat, Frangky; Tooy, Dedie; Pakasi, Sandra; Wantasen, Sofia; Pioh, Diane; Mamarimbing, Rinny; Polii, Bobby; Pongoh, Jantje; Pinaria, Arthur; Tenda, Edwin; Islam, Noorul
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.601

Abstract

Indonesia has a variety of medicinal plants that are efficacious for preventing or treating various diseases. Each region has unique medicinal plants, such as in North Sulawesi, there are many medicinal plants with local names of "Jarak" (Jatropha curcas), "Jarak Merah" (Jatropha multifida), "Miana" (Coleus Scutellarioide), and "Sesewanua" (Clerodendron Squmatum Vahl). This research applies the Convolutional Neural Network (CNN) method to identify the types of medicinal plants of North Sulawesi based on leaf images. Data was collected directly by taking photos of medicinal plant leaves and then using the augmentation process to increase the data. The first stage is conducting training and validation processes using 10-fold cross-validation, resulting in 10 classification models. Evaluation results show that the lowest validation accuracy of 98.4% was obtained from fold-4, and the highest was 100% from fold-2. The third stage was to run the testing process using new data. The results showed that the worst model produced a test accuracy of 80.91% while the best model produced an accuracy of 87.73% which means that the identification model is quite good and stable in classifying types of medicinal plants based on its leaf images. The final stage is to develop a web-based system to deploy the best model so people can use it in real-time
Sequential Pattern Mining to Support Customer Relationship Management at Beauty Clinics Setiawan, Esther Irawati; Natalie, Valerynta; Santoso , Joan; Fujisawa, Kimiya
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.602

Abstract

The increasing competition for beauty clinics, makes management need to think of methods to survive in this competition. For that, the company needs to improve CRM in its service to customers. Customer Relationship Management is a series of activities managed in an effort to better understand, attract attention, and maintain customer loyalty. Sequential Pattern Mining is one of the data mining techniques that is useful for finding patterns sequential / sequence of a set of items. The algorithm that is used is the Generalized Sequential Pattern (GSP). GSP performs candidate generation and support counting processes that is, the union of L1−k with itself which generates a candidate sequence that cannot exist as twin candidate, after that deletion candidate who does not meet the minimum support. While carrying out the process through existing data, is also carried out increasing the number of supports from the included candidates in data sequences. The output to be produced by the program are all frequent itemsets that satisfy minimum support in the form of rules. Sales transaction data will be processed by using the Generalized Sequential Pattern algorithm so that it can produce a rule, namely the purchase order that meets the minimum support. The result of the rule used by management to support enterprise CRM activities such as acquiring new customers, increasing the profits from existing customers, and retaining existing customers.
Cyberbullying Body-Shaming Levels in Adolescence Collantes, Leonel Hernandez; Saputra, Fajar Ananda; Solikhah, Putri Riadatus; Laksana, Trisna Chandra; Yakti, Novan Kuncoro; Tipagau, Jecksoniel
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.603

Abstract

Social media is a medium that teenagers very often use. Interaction media that users can use to easily interact, share, and social network without limits. The development of this social media can cause many impacts. This media will also have a harmful impact if used excessively. These problems arise in individuals who use the internet excessively, such as playing online games outside the limits of teaching to cause behavioral changes such as rudeness and aggression. Besides that, problems in the cyber world are commonly called cyberbullying. In addition, social media users easily express and publish their emotions and thoughts, including negative thoughts and emotions for others. The impact of this is the occurrence of bullying on social media. Cyberbullying, or cyberbullying, is a negotiation act that occurs and uses cyber media. Bullying often occurs through insults, threats, and humiliation on social media and text messages. The form of insult in cyberbullying is by bullying someone's physical appearance or better known as body shaming. Body shaming is a form of verbalemotional violence often not realized by the perpetrator because it is generally considered normal. Someone doing body shaming varies, from lighting the atmosphere, having fun, and inviting laughter to have reasons meant to insult

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