cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Usman Ependi
Contact Email
usmanependi@adsii.or.id
Phone
081271103018
Journal Mail Official
usmanependi@adsii.or.id
Editorial Address
Jl AMD, Lr. Tanjung Harapan, Taman Kavling Mandiri Sejahtera B11, Kel. Talang Jambe, Kec. Sukarami, Palembang, Provinsi Sumatera Selatan, 30151
Location
Unknown,
Unknown
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
 65   66   67   68   69 
Integrating the PIECES Framework with Human Computer Interaction to Evaluate User Acceptance of E-Marketplace Information Systems Fiati, Rina; Zahro, Nafi Inayati; Latifah, Noor
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.v7i4.1354

Abstract

This study evaluates user acceptance of E-Marketplace information systems by integrating the PIECES Framework with a Human–Computer Interaction (HCI) approach. This integration offers a comprehensive view of both technical system performance and user-centered interaction, particularly for users with disabilities. The PIECES Framework assesses system quality and operational effectiveness, while the HCI approach emphasizes usability, user experience, and interaction patterns that influence acceptance and satisfaction. Using an action research design, data were collected via questionnaires from a sample of 30 respondents. The findings indicate that user interest has a partial yet significant effect on behavior, while other variables jointly influence user engagement. Notably, there was a marked increase in user understanding of internet tools—from 27% initially not understanding application use to 91% demonstrating improved comprehension. This progress underscores the importance of accessible and user-friendly design in enhancing trust and perceived security. The results highlight the critical role of consistent interface design, clear navigation, and inclusive visual elements in promoting usability and satisfaction. The study offers valuable insights for system developers and researchers to improve E-Marketplace platforms by aligning technical performance with inclusive, user-centric design—ensuring accessibility for all users, including persons with disabilities, and driving greater digital inclusion in the evolving digital economy.
IoT-Based Air Quality Monitoring and Analysis at MSME Locations Fitria, Fitria; Pebriadi, Muhammad Syahid; Windarsyah, Windarsyah; Rakhmawati, Aneta; Khalid, Anhar
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.v7i4.1355

Abstract

Air is a crucial element that affects the survival of living things, but air pollution is often overlooked, especially in areas with intensive human activities, such as MSME locations. This research aims to design an Internet of Things (IoT)-based air quality monitoring device in MSME trader locations, especially in open spaces exposed to cigarette smoke and closed air-conditioned spaces. The method used was a quantitative descriptive approach with experiments, collecting primary data through an MQ-135 air quality sensor that measured the concentration of gases such as CO and NH3. The results showed that in an air-conditioned room, the gas concentration was detected at 536.00 PPM, while in the cigarette smoke area it was 197.36 PPM. A significant decrease in sensor resistance at both locations indicates the presence of air pollution that is harmful to health. Data were collected continuously for seven days. Based on OSHA exposure limits, concentrations above 50 ppm may pose health risks, indicating that the detected 536 ppm is significantly beyond safe thresholds. This device demonstrates real-time environmental monitoring applicability for MSME settings. This study proposes continuous monitoring and pollution mitigation to improve air quality and reduce health impacts.
IoT-Based Smart Classroom Prototype Using NodeMCU and Blynk for Environmental Monitoring Zilni, An; Wibisono, Iwan Setiawan
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.v7i4.1356

Abstract

The rapid advancement of the Internet of Things (IoT) has introduced numerous innovations in the education sector, one of which is the Smart Classroom concept a learning environment where interconnected devices communicate autonomously to enhance comfort, energy efficiency, attendance accuracy, and classroom safety. This study aims to design and implement an IoT-based Smart Classroom prototype utilizing NodeMCU as the main controller and the Blynk application as the platform for real-time monitoring and control of classroom conditions. Through this system, teachers and students can monitor temperature and humidity levels via mobile devices and remotely activate lights or fans without physically being in the classroom. The research employs a prototyping method comprising requirement analysis, design, implementation, testing, and evaluation to ensure that the system functions effectively and is user-friendly in a school setting. Experimental results demonstrate that the prototype operates reliably, displaying sensor data in real-time and performing automatic control actions such as activating the fan when the temperature exceeds a predefined threshold. Additionally, the system provides automatic alerts to maintain safety and comfort. Overall, the developed prototype offers a practical, low-cost, and easily deployable Smart Classroom solution that can be further enhanced through integration with online learning systems or data analytics for improved energy efficiency and sustainability.
Semantic-Enhanced News Clustering Using TF-IDF and WordNet with K-Means Hidayat, Mohammad Yusuf; Yaqin, Muhammad Ainul; Abidin, Zainal
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.v7i4.1360

Abstract

Text clustering of news articles falls under unsupervised learning, where models operate on unlabeled data unless partially annotated. K-Means Clustering remains one of the most commonly applied algorithms due to its efficiency and simplicity. Likewise, TF-IDF is a widely used approach for generating document feature matrices through statistical term weighting. Although still relevant, TF-IDF lacks the ability to represent contextual meaning, which often prevents semantically related news articles from forming coherent clusters when different syntactic variations are used. This limitation is evidenced by the baseline experiment, in which TF-IDF obtained a silhouette score of 0.011 at the optimal cluster configuration (k = 5). To overcome this limitation, this study introduces semantic enrichment using WordNet to improve similarity representation based on keywords extracted through TF-IDF, evaluated on 1000 documents sampled from 21,495 filtered records. The elbow method was applied to determine the optimal number of clusters. At the optimal k-value of 3, the proposed method achieved a silhouette score of 0.505, significantly outperforming the baseline TF-IDF representation despite utilizing fewer clusters. These results demonstrate that incorporating semantic information can enhance statistical text representations and produce more contextually coherent news clusters. To manage computational task, the model applies a first-POS strategy, where only the first synset derived from POS tagging is considered. While this reduces processing complexity, it may limit the model's ability to fully capture polysemy.
Towards a Technology-Enabled Framework for Community Healthcare: A Multi-Stakeholder Qualitative Assessment of Uganda's VHT Program Mukalere, Justine; Ssembatya, Richard; Ejiri, Annabella Habinka
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.v7i4.1361

Abstract

Community Health Worker (CHW) programs, like the VHT-Program in Uganda, play a critical role in bridging community-health system gaps, especially in resource-constrained areas. This study explored its implementation with a focus on data management, technological infrastructure, and governance, guided by the Health Metrix Network (HMN) framework. The aim was to examine the VHT-Program's implementation from a multi-stakeholder perspective in selected districts of Uganda, informing the design of a technology-enabled community health framework. A qualitative, cross-sectional design was used, gathering data through interviews and focus groups with 147 participants, including VHTs, health workers, district health officials, and community members from Kibuku, Bulambuli, and Bugweri districts. The analysis, using Braun & Clarke’s thematic method, revealed eight key themes: Health Information System Resources, Data Sources, Data Management, Leadership & Governance, Dissemination and Use, Coordinating Mechanisms, Connectivity, and Challenges & Solutions. While some HMN components were affirmed, gaps in data management, coordination, and infrastructure were identified. This informed the development of the JTM-HMN Framework, which proposes a context-specific, integrated approach to guide policy development and the implementation of technology-driven healthcare interventions.
Forensic Analysis of AI-Generated Image Alterations Using Metadata Evaluation, ELA, and Noise Pattern Analysis Ferdiansyah, Ferdiansyah; Deazwara, Muhammad Rizki Akbar; Billanivo, Reynaldi Rizki; Ardiansyah, M.; Ilham, Ilham
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.v7i4.1362

Abstract

This study develops a forensic workflow to assess the authenticity of digital images, addressing the challenge of distinguishing AI-generated content from real photographs. The goal is to analyze metadata, compression behavior, and noise characteristics to identify synthetic images. The dataset includes eight images: two original Xiaomi 14T Pro photos and six AI-generated variants from Gemini, ChatGPT, and Copilot. Metadata was extracted using ExifTool version 13.25 on Kali Linux, while Error Level Analysis (ELA) and Noise Pattern Analysis (NPA) were performed with consistent parameters on the Forensically platform. Authentic images displayed complete EXIF metadata, uniform compression patterns, and stochastic sensor noise. In contrast, AI-generated images lacked EXIF data, included XMP or C2PA provenance, exhibited localized compression anomalies, and showed smoother, more structured noise patterns. The study presents a practical and reproducible forensic workflow that integrates metadata evaluation, ELA, and noise analysis to detect synthetic content. The findings demonstrate that despite their visual realism, AI-generated images still leave detectable forensic traces, offering valuable tools for image authenticity verification.
Integrating Aspect-Based Sentiment Analysis with CSI–IPA for Telecommunications App Development Marshella, Siti Hariza; Kurniawan, Dedy; Oktadini, Nabila Rizky; Sanjaya, Rudi; Sevtiyuni, Putri Eka; Gumay, Naretha Kawadha Pasemah
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.v7i4.1363

Abstract

This study integrates Aspect-Based Sentiment Analysis with Customer Satisfaction Index (CSI) and Importance Performance Analysis (IPA) to determine priority development features in digital service applications in the telecommunications sector. A total of 10,000 MyIM3 user reviews were analyzed using sentiment analysis with Pseudo-labeling and Fine-Tuned IndoBERT, then from the results of the analysis, negative sentiment was mapped into several topics using LDA. The topic is used to compile question indicators based on the five dimensions of SERVQUAL. After the questionnaire data is declared valid and reliable, CSI and IPA analysis is carried out. A CSI value of 79.22% indicates that user satisfaction is in the "borderline" category, but several aspects still need to be improved, especially system updates (RS3), application attention to user needs (E2), and feature personalization (E3) which are in quadrant I (Concentrate Here). This hybrid approach offers novelty by demonstrating how ABSA and LDA can be systematically integrated with CSI and IPA to provide more comprehensive and user-oriented insights. The limitations of this study include focusing on negative sentiment data for feature exploration, as it is most relevant for identifying problems and opportunities for improvement and development of telecommunication digital services.
Comparative Analysis of Machine Learning Algorithms for Sentiment Classification of Discord App Reviews Rosita, Rani; Prasetyaningrum, Putri Taqwa
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.v7i4.1367

Abstract

The increasing use of digital communication applications such as Discord has generated diverse user opinions expressed through reviews on the Google Play Store. This study aims to analyze user sentiment toward the Discord application using text mining and machine learning techniques. A total of 3,000 reviews were collected through web scraping, pre-processed, labeled using a lexicon-based approach with TextBlob, and balanced using the SMOTE-Tomek method. Sentiment classification was performed into positive, negative, and neutral categories using Decision Tree, Logistic Regression, Support Vector Machine (SVM), and an Ensemble method. The Ensemble model achieved the highest accuracy of 98.67%, followed by Decision Tree (96.50%), SVM (95.83%), and Logistic Regression (90.33%). Limitations of this study include the use of lexicon-based sentiment labeling, machine translation from Indonesian to English, and initial class imbalance. Despite this strong performance, the study has limitations related to lexicon-based labeling, translation of reviews into English, and the presence of a highly imbalanced class distribution in the original dataset. Overall, the findings demonstrate that the Ensemble approach effectively improves sentiment classification accuracy and can support data-driven decision-making in application development.
Investigating Job Satisfaction Among Academic and Non-Academic Employees: Evidence from a Public University in Bangladesh Akter, Sabina; Yesmin, Farjana; Akter, Sadia; Sakib, Md. Nazmus; Sarker, Md. Mostakim
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.v7i4.1369

Abstract

This study explores job satisfaction and its determinants among academic and non-academic staff at Begum Rokeya University, Bangladesh, to identify factors influencing morale, motivation, and retention in a public higher education institution. Using a mixed-methods approach, quantitative data were gathered via a structured 5-point Likert-scale questionnaire, and qualitative insights were obtained through semi-structured interviews with a purposive sample of 50 employees. Results show moderate overall job satisfaction, with high satisfaction regarding annual leave (mean = 4.32) and work environment (mean = 4.04), but low satisfaction with promotion opportunities (mean = 2.72) and training and development (mean = 2.78). The scale’s high reliability (Cronbach’s α = 0.993; standardized α = 0.994) supports the validity of the findings. Herzberg’s motivation-hygiene theory highlights promotion and professional development as key hygiene factors. This research offers crucial insights for improving promotion policies and training systems and calls for future longitudinal studies across Bangladesh’s higher education sector.
YOLOv11-Based Automated PPE Detection System for Workplace Safety Monitoring in Electric Power Distribution Operations Ordrick, Jevon; Wibowo, Galih Hendra; Fahmi, Arif; Kurniawan, Indra; Haq, Endi Sailul
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.v7i4.1379

Abstract

Manual monitoring of Personal Protective Equipment (PPE) compliance in electric power distribution is prone to human error, limited supervision, and geographically dispersed work sites. This study proposes an automated PPE detection system using the YOLOv11 deep learning model to enhance safety monitoring at PT PLN (Persero) UP3 Banyuwangi. A dataset of 589 images containing 1,425 labeled PPE instances across seven categories was used to train the YOLOv11s model. The system was deployed via a web-based application with adjustable detection thresholds and validated through interviews with three OHS supervisors. It achieved 94.0% precision, 90.1% recall, and 92.8% mAP@50, with perfect detection for persons and near-perfect results for full-body harnesses. The application processed images in 2–3 seconds on standard CPU hardware, supporting automated documentation for compliance reporting. This is the first known YOLOv11-based PPE detection system tailored to electric power distribution settings. While results are promising, limitations include a small validation set and lower accuracy in detecting safety boots. Future work should explore real-time video analysis, system integration, and long-term studies on safety compliance improvements.

Page 68 of 69 | Total Record : 682

 65   66   67   68   69 

Filter by Year

2019 2025


Reset
Filter By Issues
All Issue Vol 7 No 4 (2025): December Vol 7 No 3 (2025): September Vol 7 No 2 (2025): June Vol 7 No 1 (2025): March Vol 6 No 4 (2024): December Vol 6 No 3 (2024): September Vol 6 No 2 (2024): June Vol 6 No 1 (2024): March Vol 5 No 4 (2023): Journal of Information Systems and Informatics Vol 5 No 3 (2023): Journal of Information Systems and Informatics Vol 5 No 2 (2023): Journal of Information Systems and Informatics Vol 5 No 1 (2023): Journal of Information Systems and Informatics Vol 4 No 4 (2022): Journal of Information Systems and Informatics Vol 4 No 3 (2022): Journal of Information Systems and Informatics Vol 4 No 2 (2022): Journal of Information Systems and Informatics Vol 4 No 1 (2022): Journal of Information Systems and Informatics Vol 3 No 4 (2021): Journal of Information Systems and Informatics Vol 3 No 3 (2021): Journal of Information Systems and Informatics Vol 3 No 2 (2021): Journal of Information Systems and Informatics Vol 3 No 1 (2021): Journal of Information Systems and Informatics Vol 2 No 2 (2020): Journal of Information Systems and Informatics Vol 2 No 1 (2020): Journal of Information Systems and Informatics Vol 1 No 2 (2019): Journal of Information Systems and Informatics Vol 1 No 1 (2019): Journal of Information Systems and Informatics More Issue