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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 682 Documents
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Empirical Evaluation of Decentralized Genomic Data Computation Using Bacalhau and IPFS Triaji, Bagas; Badiyanto, Badiyanto; Afif, Justivan Intifadhah
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1311

Abstract

Large-scale genomic analysis typically relies on centralized infrastructures, creating conflicts between collaborative needs and data sovereignty regulations. This study solves this dilemma by evaluating a decentralized architecture designed to facilitate secure, inter-institutional genomic computation without moving raw data. We integrated Bacalhau for orchestration and IPFS Cluster with CRDT consensus for storage, employing AES-256 encryption. A quantitative evaluation was conducted on AWS using five t3.medium nodes to simulate a resource-constrained hospital network. We tested three scenarios: a centralized baseline (SSH+SCP), an ideal decentralized workflow, and a "chaos" scenario involving active network fault injection. While the centralized baseline was the fastest (Mean=37.69s), the decentralized architecture incurred a manageable ~30% overhead under ideal conditions (Mean=49.22s, SD=1.58s). Critically, under chaos fault injection, although execution time increased to 90.67s (SD=17.84s), the system achieved a superior 100% job completion rate compared to the fragile baseline. This research quantifies the trade-off between execution speed and system resilience in a healthcare context. We demonstrate that this architecture prioritizes data sovereignty and high availability over raw speed, offering a proven model for privacy-critical Decentralized Science (DeSci) collaborations.
Quantum Computing Cryptography: A Systematic Review of Innovations, Applications, Challenges, and Algorithms Maitireni, Peter; Ncube, Vusumuzi; Ndlovu, Belinda; Sibanda, Thando
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1331

Abstract

This study explores how to build quantum-resistant systems to safeguard digital infrastructure in the post-quantum era by uncovering the innovations, applications, algorithms, and challenges of Quantum Computing cryptography. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach a search was conducted across the following databases for the years 2021–2025: PubMed, IEEE Xplore, ScienceDirect, SpringerLink, and Google Scholar. We shortlisted 15 studies from 519 screened articles for a comprehensive evaluation based on their relevance. Findings show strong adoption in finance, healthcare, IoT, cybersecurity, and e-government, with lattice-based PQC emerging as the most dominant cryptographic family, followed by QKD and hybrid PQC–QKD models. The review highlights key obstacles, including transition complexity, lack of global standards, high implementation costs, and integration difficulty. The study contributes by providing the first sector-aligned synthesis of innovations, identifying algorithmic trends, and mapping global research disparities through a conceptual model. It also presents a structured set of future research directions to guide policymakers, cryptographers, and practitioners preparing for quantum-enabled threats.
Adaptive-Delta ADWIN: A Framework for Stable and Sensitive Intrusion Detection in Streaming Networks Sebopelo, Rodney Buang
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1336

Abstract

Intrusion Detection Systems (IDS) must adapt to network traffic streams where concept drift alters the normal and malicious behaviors. The traditional drift detectors with fixed sensitivity parameter () fail to balance responsiveness and stability, reducing detection reliability. This study introduces Adaptive−Delta ADWIN framework that adjusts through two online controllersthe Volatility Controller (VC) and AlertRate Controller (ARC) to improve the sensitivity while maintaining stability. The experiments were evaluated on the CICIDS2017 dataset using multiclass ensemble of Hoeffding Adaptive Trees, the framework achieved 0.930.95, surpassing fixed baselines by up to 6.6%. The false positive and false negative rates were reduced by 50% and 30%. Overall, the results confirm that Adaptive ADWIN enhances multiclass IDS performance between detection sensitivity and operational stability in the realtime network conditions.
K-Means Clustering with Elbow Method for Stunting Risk Detection in Toddlers Using Anthropometric and Nutritional Data Darmayanti, Irma; Saputra, Dhanar Intan Surya; Wijaya, Anugerah Bagus; Wijanarko, Andik; Fortuna, Dewi; Putranto, Aldrian Firmansyah
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1337

Abstract

Stunting remains a critical public health challenge in Indonesia, primarily due to inadequate nutrition and recurrent infections in early childhood. This study aimed to identify patterns of stunting risk by integrating anthropometric and dietary data, specifically sugar consumption, using an unsupervised machine learning approach. A total of 20 toddlers aged 12-59 months from Purwokerto Selatan participated. Anthropometric data (age, weight, height) and dietary intake (sugar consumption, snack frequency) were collected via a caregiver questionnaire. K-Means clustering was applied, with the optimal number of clusters determined using the Elbow Method (K=2). Two clusters were identified: Cluster 0, with a lower risk of stunting, and Cluster 1, with a higher proportion of toddlers at risk. Cross-tabulation with stunting status validated this, showing that Cluster 1 contained more children with "Potential" stunting. Internal validation using the Silhouette score (0.252) and PCA visualization confirmed the clustering's robustness. This study demonstrates the potential of combining anthropometric and dietary data for stunting risk profiling, suggesting a complementary approach for growth monitoring programs and targeted interventions.
AIDA-Based Analysis of TikTok Live Marketing at Bin Dawood Boutique Purwokerto Maharani, Revalyna Octavia; Pritama, Argiyan Dwi; Oktaviana, Luzi Dwi
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1339

Abstract

This study aims to analyze the TikTok Live strategy implemented by Bin Dawood Butik Purwokerto using the AIDA model as an analytical framework. This research employed a descriptive qualitative design, through observations of 10 TikTok Live sessions, in-depth interviews with a marketing administrator and a live host, and documentation. Data were analyzed through reduction, presentation, and conclusion drawing based on the AIDA framework, with triangulation applied to ensure validity. Bin Dawood Boutique’s TikTok Live strategy effectively implements the AIDA model. The attention stage is built through persuasive greetings, engaging visuals, and broadcast scheduling that aligns with audience activity patterns. The interest stage is strengthened through the use of TikTok’s interactive features and the delivery of clear, responsive product information. The desire stage develops through host transparency, emphasizing product benefits, and strategic urgency. The action stage is driven by the use of clear CTAs and seasonal factors, such as the Eid al-Fitr period and payday, which encourage consumers to make transactions. Cumulative TikTok sales reached more than 26,900 products, confirming TikTok Live’s significant contribution to overall sales performance. This study provides an empirical overview of how a local fashion business operationalizes each stage of the AIDA model on TikTok Live. As a limitation, the study focuses on a single case and relies on qualitative data, which may constrain generalization.
Emerging Trends in Digital Transformation and Information Systems by Bibliometric Analysis in the United States Islam, Mirazul; Islam, Md Ahadul; Saha, Raju; Hossain, Didar; Rahman, Md. Mahfuzur
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1340

Abstract

This bibliometric analysis examines the evolving trends of digital transformation (DT) and information systems (IS) in U.S. businesses. It explores how technology—focused on strategy, efficiency, innovation, and customer engagement—is reshaping organizations and workplaces. Using a PRISMA-based systematic review and data from Scopus (2016–2026), the study applies the Bibliometrix R package to assess publication patterns. Results show significant growth, with 2,692 documents reflecting a 43.58% annual increase and 18.39% involving international collaboration. Key themes include AI/ML integration in business processes, digital sustainability, and IS as a strategic driver for business model evolution. U.S. businesses are increasingly aligning digital transformation with sustainability goals. This study addresses a key research gap by offering detailed insights into DT and IS impacts on operations and sustainability practices. It underscores the need for integrated socio-technical strategies, responsible data governance, and global collaboration to foster innovation and bridge digital divides.
Multi-Tier Architecture Design for Scalable and Effective Non-Formal Learning: A Redesign of Serat Kartini Women's School LMS Ardana, Primavieri Rhesa; Trisnapradika, Gustina Alfa
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1341

Abstract

Non-formal education plays a vital role in empowering women in rural areas of Central Java, Indonesia. However, the existing Learning Management System (LMS) of Woman School Serat Kartini, built on a monolithic Laravel architecture, suffers from significant performance degradation and scalability limitations under growing user loads and shared hosting constraints. This leads to high latency, frequent session interruptions, and reduced participation, ultimately undermining learning effectiveness. This study redesigns the LMS using a multi-tier application architecture through the Design Science Research (DSR) methodology. The proposed blueprint separates the system into four independent tiers: Presentation (Next.js for users, React.js for administrators), Logic (Express.js for API Layer), Cache (Redis with cache-aside strategy), and Data (MySQL). The design artifacts include detailed architecture diagrams, ERD, use case, and sequence diagrams. Conceptual evaluation demonstrates that the multi-tier approach enhances modularity, reduces latency, supports horizontal scalability, and improves resource efficiency , ensuring reliable access for women learners with limited digital literacy and unstable internet connectivity. The redesigned LMS conceptually strengthens learning accessibility, engagement, and program sustainability in resource-constrained non-formal education contexts. This research is limited to the conceptual design phase without implementation or empirical testing.
Sentiment Analysis of User Reviews for the PLN Mobile Application Using Naïve Bayes and Long Short-Term Memory Ayomi, Jose Mario; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Widiartin, Tjatursari
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1342

Abstract

This study explores large-scale sentiment analysis of user reviews for the PLN Mobile application to better understand public perception and provide quantitative insights for improving digital electricity services in Indonesia. Addressing the lack of benchmarks for Indonesian public-service apps—where prior studies rely on smaller datasets and traditional machine learning—this research positions sentiment analysis as a tool for continuous user experience monitoring. A total of 50,000 Indonesian-language reviews from Google Play were collected and pre-processed using cleaning, case folding, tokenization, stopword removal, normalization, and stemming. Sentiments (positive, neutral, negative) were assigned using a domain-specific Indonesian sentiment lexicon, yielding approximately 40% positive, 35% neutral, and 25% negative labels. Two models were applied: Multinomial Naïve Bayes using TF-IDF features and a Long Short-Term Memory (LSTM) model with 100-dimensional word embeddings and a 128-unit LSTM layer. Naïve Bayes achieved 70.89% accuracy (F1-score: 0.6964), while LSTM outperformed it with 98.02% accuracy (F1-score: 0.9800). These results highlight the superiority of deep learning in sentiment monitoring and offer a scalable framework to help PLN and policymakers enhance digital public service delivery.
Cybersecurity Trends in Digital Marketing for Public Health: A PRISMA based Bibliometric Analysis Sakib, Nazmus; Faraji, Mahfujur Rahman; Shovon, Fatihul Islam; Naiem, Md. Julker; Hossain, MD. Tofajjal; Mim, Taslima Akter; Shanta, Sadia Arfin
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1343

Abstract

This study conducts a bibliometric analysis of digital marketing in public health through the lens of cybersecurity, aiming to evaluate research trends from 2015 to 2025. It identifies key developments, major contributors, and provides guidance for future studies. A total of 1,191 documents were analyzed, revealing a significant annual growth rate of 32.01% and an average of 19.01 citations per document. The analysis explores how digital marketing for public health intersects with cybersecurity, a domain that remains underexplored. Data collection and visualization were conducted using Scopus, Biblioshiny, and VOSviewer, with article selection guided by the PRISMA methodology. Results indicate consistent growth in publications over the decade, though a noticeable decline occurred post-COVID-19 in 2020. The study offers a comprehensive mapping of existing literature and highlights the strategic importance of integrating cybersecurity into digital health marketing to protect patient data, maintain public trust, and enhance health outcomes. It provides valuable insights for researchers, policymakers, and practitioners aiming to improve the security and effectiveness of digital health communication in an increasingly connected world.
Challenges and Barriers of Technology Adoption Among Women in Open and Distance Learning: Evidence from Botswana Majoo, Pulafela Akofhang; Rafifing, Neo; Mabina, Alton; Tlhoolebe, Joyce; Gadilatolwe, Innocent
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1349

Abstract

This study explores gender-specific challenges that affect women’s adoption of technology in Open and Distance Learning (ODL) in developing countries, focusing on Botswana. It addresses the limited empirical understanding of how socio-economic, cultural, and digital literacy factors shape women’s ability to engage with technology-mediated education. A cross-sectional survey was conducted with 20 women enrolled in ODL programs, collecting data on technology access, digital competence, socio-economic background, and perceptions of institutional support. Descriptive and inferential statistical analyses, including correlations and chi-square tests, were conducted using SPSS. The findings show that limited digital literacy and poor internet access are the main barriers, while higher education and income levels positively impact technology engagement. Socio-cultural norms and institutional support also play a role, though shifting gender roles are reducing traditional constraints. This study highlights the intersection of individual competencies and contextual factors, providing evidence of both technological and socio-cultural determinants of women’s participation in ODL. The results inform policy and suggest areas for future research on inclusive digital education strategies.

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