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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 653 Documents
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A Hybrid Framework for Enhancing Privacy in Blockchain-Based Personal Data Sharing using Off-Chain Storage and Zero-Knowledge Proofs Mandinyenya, Godwin; Malele, Vusumuzi
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1119

Abstract

Blockchain technology presents transformative opportunities for secure personal data sharing, particularly in healthcare, finance, and identity management. However, its widespread adoption is constrained by challenges such as limited scalability, privacy concerns, and conflicts with regulatory frameworks like the General Data Protection Regulation (GDPR). This study introduces a novel hybrid framework that integrates the InterPlanetary File System (IPFS) for off-chain storage with Zero-Knowledge Proofs (ZKPs) to enhance privacy, ensure regulatory compliance, and reduce on-chain storage demands. Employing a Design Science Research (DSR) methodology, the framework was developed and validated using Ethereum and Hyperledger Fabric, guided by insights from a systematic review of 180 studies from 2018 to 2023. Empirical evaluations revealed a 75% reduction in blockchain storage, 98% GDPR compliance, and zk-SNARK proof verification times below one second. The framework also enables GDPR-compliant erasure by removing encrypted off-chain data while preserving on-chain auditability. Despite challenges such as IPFS latency and trusted setup complexities, the solution offers a scalable and privacy-preserving architecture applicable to real-world domains, especially in privacy-critical environments like healthcare and finance by resolving blockchain’s GDPR compliance paradox.
Gender Motivations for TikTok Content Creation: A Comparative Study of Male and Female Students’ University Students Ndou, Ananias; Magcaba, Mfanafuthi; Mthembu, Nompumelelo; Jugoo, Vikash; Mutanga, Murimo Bethel
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1130

Abstract

TikTok has rapidly become a leading platform for youth self-expression and digital participation, yet little is known about how gender influences motivations for content creation. This study explores gender-based differences among South African university students, addressing a key gap in the literature. Using a mixed-methods design, 100 students (50 male, 50 female) were surveyed and focus groups with 25 participants were conducted to examine content types and motivational drivers, over a three-month period. Findings reveal clear distinctions: female students are primarily motivated by self-expression, social connection, and stress relief, favoring fashion, lifestyle, and dance content. Male students, by contrast, focus on entertainment, follower growth, and raising awareness, often creating comedy and educational videos. These patterns reflect broader social norms and platform dynamics, emphasizing different gratifications by gender. The study is guided by the Uses and Gratifications Theory in understanding these gendered motivations is essential for fostering more inclusive and responsive social media environments. It offers practical insights for educators designing digital literacy interventions, as well as for platform developers aiming to enhance inclusivity and user engagement.
Development and Capability Evaluation of a Firebase-Based Pharmacy Inventory System Using COBIT 2019 Muttaqin, Alif Noorachmad; Sandy, Muhammad Dwi Hary; Lubis, Muharman
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1139

Abstract

Pharmacy inventory control systems require proper and timely data management to be able to supply medicines and function as such. The study conceptualized and tested a Firebase-based system of pharmacy inventory control. The system was conceptualized in the web and Android platforms with the key objectives of enabling real-time synchronization, tracking, and reporting functionalities. Capability measurement from utilizing the COBIT 2019 method was utilized in evaluating system governance and operational performance. Four key processes are BAI03 (Identification and Build of Managed Solutions), DSS01 (Managed Operations), DSS02 (Managed Service Requests and Managed Incidents), and MEA01 (Managed Performance Monitoring) were chosen shortlisted and mapped to system indicators. Seven pharmacy employees were subjected to the assessment with a Likert-scale questionnaire. The results showed that three processes attained Capability Level 4 (Predictable) and one attained Capability Level 5 (Optimizing), i.e., the system performs predictably and allows continuous improvement. Weakness points despite deployment of the system with proof of handling data with ease and responsiveness were the fact that the sample size of respondents was small and one pharmacy only had it deployed. Much more must be done to experiment with the system in different environments and explore integration with third-party platforms for further scalability and adherence to governance.
Comparison of RNN and LSTM Classifiers for Sentiment Analysis of Airline Tweets Ahmed, Rogaia Yousif; Yuosif, Noon Fahmi; Ahmed, Sarmed Awad; Mohammed, Al-Baraa Ali
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1140

Abstract

This study examines the application of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models for sentiment analysis of airline-related tweets, focusing on customer feedback directed at U.S. airlines on the X platform (formerly Twitter). The objective was to utilize these deep learning models to identify sentiment trends within text data and compare their performance in terms of computation time. The analysis was conducted on a 14,640-imbalanced dataset of classified tweets from February 2015 as positive, negative, or neutral. Both models were trained under identical conditions using Term Frequency-Inverse Document Frequency (TF-IDF) and Word2Vec for feature extraction. LSTM achieved 74% accuracy with AUC scores of 0.84, 0.90, and 0.89. RNN achieved 72% accuracy with AUC scores of 0.78, 0.87, and 0.85. In terms of time efficiency, RNN outperformed LSTM, requiring 57.16 seconds for training and 0.52 seconds for testing, compared to LSTM’s 82.40 and 0.82 seconds. Time performance was also evaluated per sentiment class, and RNN consistently outperformed LSTM. These results highlight the trade-off between accuracy and computational cost. Limitations include dataset imbalance and LSTM’s slower computation due to its internal gate mechanisms. Future work could prioritize integrating hybrid models and may use data imbalance techniques to improve sentiment classification.
Deep Learning and Statistical Models to Analyse Online Misinformation and Hate Speech Impact on African Youth Gyimah, Esther; Dake, Delali Kwasi; Mawusi, Confidence; Ofori, Elijah
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1141

Abstract

This study examines the perceptions, behaviour, and digital experiences of African youth in relation to online misinformation and hate speech. Using a large-scale, cross-national survey with 10,005 valid responses, the research relies on both statistical clustering and deep learning-based autoencoder models to group youth together based on their trust in information, concern about misinformation, verification behaviours and platform usage. The dual-method analysis highlights three distinct behavioural and attitudinal clusters of youth, denoting different levels of digital skeptical engagement, exposure, and civic engagement. The findings highlight the heterogeneity within the youth population and emphasize that a one-size-fits-all approach to combating misinformation is insufficient. Notably, youth with high concern also demonstrated strong verification habits, while less engaged clusters exhibited low concern and limited digital resilience. These insights offer a foundation for designing cluster-specific interventions and media literacy strategies that are regionally and behaviourally responsive. This combination advances research through unsupervised deep learning on large social survey data, as well as demonstrating the utility of deep learning in revealing latent behaviours. The implications of this study's findings are timely for educators, policy makers and digital platforms more broadly, that want to foster informed and safe digital participation for African youth. As scalable, data-driven framework is a contribution towards an inclusive digital policy package for varied youth realities that exist in an African context.
Optimizer Evaluation for Maize Leaf Disease Using Transfer Learning with MobileNetV3-Small Athallah, Dhea Fesa; Budiman, Thomas; Sianipar, Anton Zulkarnain
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1144

Abstract

Manual identification of maize leaf disease presents significant challenges, including time- consuming processes, dependence on expert availability, and a high risk of misdiagnosis due to similar symptoms among different diseases. These limitations often lead to delays in disease management, unstable crop yields, and economic losses for farmers. This study aims to address these issues by evaluating the performance of different optimizers in classifying maize leaf disease using transfer learning with the MobileNetV3-Small architecture. A total of 2,850 images of maize leaf disease were used and divided into training, validation, and testing sets. Model evaluation involved systematically comparing the Adam, RMSprop, and SGD optimizers by training each configuration under identical conditions and assessing the resulting model performance. The results show that the RMSprop optimizer provides the best performance with 92.98% accuracy, 93.08% precision, 92.98% recall, and 92.98% F1-score. Based on the evaluation, selecting an appropriate optimizer is essential to improve accuracy and reliability of transfer learning models in maize leaf disease classification. These findings highlight the potential to advance smart agricultural systems by enabling more accurate disease detection, which can reduce crop failure risks and enhance disease management in maize production.
Systematic Review of Augmented Reality Applications in Wayang Heritage Preservation Hermawan, Hellik; Saputra, Dhanar Intan Surya; Albana, Ilham; Ramadhan, Muhammad Bintang; Mustofa, Dinar
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1145

Abstract

This study presents a systematic literature review on Augmented Reality (AR) in Wayang from 2020 to 2025. AR has become an innovative solution that combines education and entertainment to increase the engagement of the younger generation and expand access to traditional Wayang art. This study examines the trend of AR in Wayang, including design approaches and user interaction strategies, as well as the benefits and challenges of implementing this technology. It also identifies research gaps and future development directions. This review discusses explicitly the application of AR to various forms of Wayang, including Wayang Kulit, Wayang Golek, and other traditional variants, while excluding Virtual Reality (VR) and other digital art forms. The results indicate that AR applications based on mobile platforms with gesture interaction and gamification effectively enrich the user experience in digital Wayang performances. However, significant challenges related to technological limitations, cultural sensitivity, and involvement of indigenous communities still need to be overcome. This study recommends a multidisciplinary and collaborative approach to developing AR Wayang, enabling authentic and sustainable cultural preservation. These findings are expected to serve as the basis for inclusive digital cultural innovation, which will have a positive impact on preserving Wayang's cultural heritage.
Maternal and Child Health Services Mobile Application Prototype: A Case Study of Puskesmas Sungai Duren Muara Enim Regency Rasmila, Rasmila; Amalia, Rahayu; Adryansyah, Muhammad Rizqi Hidayah; Juniar, Kanero
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1125

Abstract

The Sungai Duren Community Health Center (Puskesmas), located in Muara Enim Regency, provides essential maternal and child health services. Currently, patient registration and data management are conducted manually using patient data books, leading to inefficiencies, errors, and data loss. This research aims to develop a UI/UX mobile application that enhances maternal and child health services at the health center. The study employs the Design Sprint 2.0 methodology, a rapid, iterative, and user-centered design approach consisting of five stages: Understand, Define, Decide, Prototype, and Test. The design of the application was created using Figma, and its effectiveness was evaluated through usability testing, using the System Usability Scale (SUS) and Net Promoter Score (NPS). The results of the study show that the application improves operational efficiency, enhances user satisfaction, and provides better access to health data, demonstrating the potential for scalable and replicable solutions in rural and underserved healthcare settings.
Blockchain and IoT for Sustainable Agriculture: Innovations and Impacts Elegbeleye, Femi Abiodun; Oguntona, Olusegun; Elegbeleye, Ife
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1136

Abstract

The integration of Blockchain and the Internet of Things (IoT) is emerging as a transformative force in sustainable agriculture. This review explores the synergistic potential of these technologies to enhance transparency, traceability, resource efficiency, and resilience in agricultural systems. We conducted a systematic review of peer-reviewed articles and conference proceedings published between 2015 and 2024, sourced from databases such as IEEE Xplore, Scopus, ScienceDirect, and SpringerLink. Studies were selected based on relevance to agricultural sustainability, the implementation of IoT and blockchain, and empirical or conceptual insights. The findings reveal that IoT devices enable real-time data collection and monitoring, while blockchain ensures secure, immutable records for supply chain transparency and smart contracts. Despite their promise, challenges persist, including high implementation costs, scalability issues, and limited digital infrastructure in rural areas. The review underscores the need for collaborative frameworks and policy support to foster adoption and recommends future research to focus on hybrid models and localized applications.
Mapping the Global ICT Research Trends in the Construction Sector Emere, Chijioke Emmanuel; Oguntona, Olusegun Aanuoluwapo
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1138

Abstract

Information and communication technology (ICT) has not been widely adopted in the construction sector, despite its promise to improve productivity, safety, communication, efficiency, and sustainability. Prior research has made clear that further research and development in this field are required to improve its application for project delivery and organisational performance, particularly in developing countries. To determine the area of focus of earlier studies, this paper reviewed ICT in fields relevant to construction. Utilising a bibliometric methodology, the data for this study were taken from the Scopus database. Keyword searches were used to search the database, such as “Information communication technology/technologies”, “Information communication”, “Communication technology”, and “Construction or Construction industry”, to obtain pertinent papers. The papers analysed were 96 in number from 2014-2024. Using VOSviewer, a network and overlay visualisation map of the co-occurrence keywords was produced based on the gathered bibliographic data. The findings indicated that earlier research in ICT gave priority to information and data management, project design, sustainable project management, power transmission and smart grids, construction project communication, and safety management and training. Furthermore, research in this area is currently concentrating on big data applications, smart city applications, and sustainable development applications. The results highlight a knowledge vacuum in which South American and African nations might investigate to enhance construction project delivery and organisational performance. This work adds to the conversation around ICT, which has not gotten much attention in recent scientometric and bibliometric research.

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