Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

IJISCS (International Journal of Information System and Computer Science)

ijiscs
Website

Published by Institut Bakti Nusantara

ISSN : 25980793 EISSN : 2598246X DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

The IJISCS (International Journal of Information System and Computer Science) is a publication for researchers and developers to share ideas and results of software engineering and technologies. These journal publish some types of papers such as research papers reporting original research results, technology trend surveys reviewing an area of research in software engineering and technologies, survey articles surveying a broad area in software engineering and technologies. The scope covers all areas of software engineering methods and practices, object-oriented systems, rapid prototyping, software reuse, cleanroom software engineering, stepwise refinement/enhancement, ambiguity in software development, impact of CASE on software development life cycle, knowledge engineering methods and practices, formal methods of specification, deductive database systems,logic programming, reverse engineering in software design, expert systems, knowledge-based systems, distributed knowledge-based systems, knowledge representations, knowledge-based systems in language translation & processing, software and knowledge-ware maintenance, Software Specification and Modeling, Embedded and Real-time Software (ERTS), and applications in various domains of interest.

Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi

Articles 141 Documents

11 12 13 14 15

DESIGN OF SAVINGS AND LOAN APPLICATIONS FOR ANDROID-BASED WOMEN'S GROUPS Fauzi Fauzi; Sephia Nuraini; Sahrul Gunawan
IJISCS (International Journal of Information System and Computer Science) Vol 9, No 3 (2025): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v9i3.1875

Many savings and loan records in farmer women groups are still done manually using books, which can risk causing errors in recording. This is the background for the development of an offline-based android application that can help the VSLA (Village Saving and Loan Association) savings and loan recording process. The purpose of this research is to build an easy-to-use savings and loan recording application, with a simple appearance and according to the needs of users at the rural community level. Application development is carried out using the kodular platform by utilizing TinyDB local storage so that applications can be used offline. The prototype method used in this study allows the development of the system to be carried out in stages according to user input and requirements. The system is designed using the Unified Modeling Language (UML) approach, which consists of a use case diagram, class diagram, and activity diagram. Group financial management becomes easier and more efficient. With the system created offline-based, the application has proven to be relevant for use in areas that have limited internet connection issues. It is hoped that this research can contribute to efforts to digitize the community financial system, especially for farmer women groups.

THE USE OF ARTIFICIAL INTELLIGENCE IN THE DEVELOPMENT OF AN ORDERLY TRAFFIC EDUCATION POSTER FOR THE PESAWARAN POLICE BASED ON MOBILE WEB TO IMPROVE STUDENT LITERACY Triyas Hastomo; Tuti Puspitasari
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 1 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i1.1881

Students' awareness of traffic discipline remains relatively low, as indicated by the high rate of violations and accidents among school-aged individuals. Conventional educational methods are considered less effective in engaging students in the digital era. The research problem focuses on how to develop a technology-based learning media that can enhance students’ understanding and engagement in traffic regulations. This study aims to develop and implement an Artificial Intelligence (AI)-based traffic education application that is interactive, adaptive, and user-friendly for high school students. This research employs the Research and Development (R&D) method, including stages of needs analysis, system design, mobile application development, AI implementation, and user testing. System evaluation was conducted involving 48 student respondents using a Likert-scale questionnaire covering interface, system security, and usability aspects. The results indicate that the application achieved a success rate of 86.00%, categorized as very successful. The usability aspect obtained the highest score of 88.50%, followed by interface (86.50%) and system security (83.00%). These findings demonstrate that the application effectively improves students’ understanding, enhances interactive learning experiences, and is easy to use. Therefore, the application is considered feasible as an AI-based educational tool to improve traffic safety literacy among high school students.

IOT AND ML-POWERED CYBER-PHYSICAL FRAMEWORK FOR REAL-TIME URBAN FLOOD RESILIENCE WITH GEOSPATIAL VISUALIZATION Emmanuel Ayobami Mesioye; Johnson Bisi Oluwagbemi; Shade Racheal Akinbo; Mathew Oluwatosin Esan
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 1 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i1.1877

Urban flooding remains a disastrous challenge for rapidly expanding cities in developing nations. Despite the fact deep learning models and IoT sensing are individually established in hydrology, their seamless integration into a unified, cost-effective Cyber-Physical System (CPS) specifically architected for data-scarce and infrastructure challenged environments remains a critical research gap. This research contributes a novel, end-to-end framework that bridges this divide by harmonizing three distinct pillars: a low-cost, energy-autonomous IoT sensor network, a hybrid CNN-LSTM predictive model, and a dynamic geospatial visualization dashboard. Unlike conventional systems designed for data-rich environments, our framework is contextually adapted for the unique topographical and socio-technical realities of Nigerian urban centers. Validated through a six-month deployment in the high-density Ajeromi-Ifelodun region of Lagos, the system achieved a Nash-Sutcliffe Efficiency (NSE) of 0.89 and a critical 4.5-hour forecast lead time.

REAL-TIME DETECTION OF PROHIBITED OBJECTS IN PUBLIC SPACES BASED ON IOT AND DEEP LEARNING Donatien Kadima Muamba; David Muanza Lubukayi; Ali Akake Nengo
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 1 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i1.1878

Security in public spaces is a major challenge in the face of diversifying threats. Traditional video surveillance systems, relying on continuous human supervision, have limitations in terms of responsiveness and reliability. This article proposes an intelligent system for detecting prohibited objects, combining the Internet of Things (IoT) and deep learning. The architecture is based on an embedded ESP32-CAM module for image acquisition and a backend server using a deep learning model for analysis. Experimental results show an overall accuracy of 92.8%, demonstrating the suitability of this approach for real-time automated surveillance applications

IMPLEMENTATION OF NAIVE BAYES ALGORITHM FOR PREDICTION OF THE SPREAD OF DENGUE HEMORRHAGIC FEVER Irma Rosita; Muhamad Muslihudin
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 1 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i1.1882

Dengue Hemorrhagic Fever (DHF) remains a significant public health problem in Indonesia, particularly in regions with environmental conditions that support the growth of Aedes aegypti mosquitoes. This study aims to implement the Naive Bayes algorithm to predict the distribution of DHF cases in the working area of Wates Public Health Center, Pringsewu Regency, Lampung. The research employs a quantitative approach using data mining techniques, including data collection, preprocessing, modeling, and evaluation stages. The dataset consists of 260 DHF cases in 204-2025 categorized into acute, subacute, and non-acute conditions. The results indicate that the Naive Bayes algorithm achieved an accuracy of 65.8%, with a recall value of 0.658 and an F1-score of 0.556. The analysis also shows that most cases fall into the acute category, and there is no significant relationship between gender and disease severity. Although the AUC and MCC values are relatively low, the model provides an initial insight into the distribution pattern of DHF. Therefore, the Naive Bayes algorithm can be utilized as a decision support system to determine priority areas for intervention and as an early warning system to improve the effectiveness of DHF control.

USABILITY EVALUATION OF KENANGAN VIP FEATURE IN THE KOPI KENANGAN APPLICATION AT NGALIYAN OUTLET SEMARANG Ireneus Pradipta Prabaswara; Florentina Yuni Arini
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 2 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i2.1896

The rapid growth of digital technology has encouraged companies to enhance customer engagement through mobile applications. One such innovation is the Kenangan VIP feature in the Kopi Kenangan mobile application, a tiered loyalty program designed to improve customer retention and satisfaction. Despite its strategic role in supporting customer loyalty, no formal usability evaluation had previously been conducted. The results revealed an average SUS score of 72.32, which falls within the “Good” category and exceeds the global SUS benchmark score of 68. The findings indicate that the Kenangan VIP feature is generally perceived as easy to use, efficient, and satisfactory. Overall, the study concludes that Kenangan VIP successfully supports customer interaction and loyalty, while targeted usability enhancements could further improve user experience and strengthen customer retention

DEVELOPMENT AND USABILITY EVALUATION OF ANDROID-BASED INTERACTIVE LEARNING MEDIA FOR SALAFIYAH ISLAMIC BOARDING SCHOOL STUDENTS Dhun Naja Rifqi; Suyono Suyono; Muhammad Rifai
IJISCS (International Journal of Information System and Computer Science) Vol 9, No 1 (2025): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v9i1.1921

The digital transformation of education presents opportunities to enhance learning accessibility while preserving traditional instructional practices in Islamic boarding schools. This study aims to develop Android-based interactive digital learning media tailored to the educational characteristics of Al-Wustho Salafiyah Islamic Boarding School, Indonesia. The proposed application integrates mobile learning principles, multimedia instructional design, and traditional Islamic learning approaches, particularly sorogan and bandongan. The system incorporates four main interfaces: a splash screen, main dashboard, learning materials page, and interactive multimedia learning page. Educational features include digital Islamic textbooks, instructional videos, audio lessons, and interactive exercises. A black-box testing framework comprising twelve scenarios was formulated to evaluate three dimensions: user interface functionality, usability-related operations, and basic security mechanisms. The proposed evaluation covers navigation, multimedia accessibility, learning activities, authentication, and access control. The study contributes a context-sensitive digital learning design that aligns mobile technology with traditional Islamic educational practices. However, empirical usability and learning effectiveness remain to be established through user testing and educational assessments. The proposed application provides a foundation for future technology-supported learning innovation in Salafiyah Islamic boarding schools

DEEP Q-NETWORK-BASED ADAPTIVE EDGE INTELLIGENCE FOR ENERGY-EFFICIENT AIR QUALITY MONITORING IN IOT NETWORKS Donatien KADIMA MUAMBA
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 2 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i2.1905

The rapid deployment of Internet of Things (IoT) networks enables environmental monitoring, but conventional fixed-interval sensing causes excessive energy consumption, communication overhead, and limited adaptability. This study proposes an adaptive edge intelligence framework using Deep Q-Network (DQN) for energy-efficient air quality monitoring. The system integrates environmental sensors with an ESP32-based edge node to measure PM2.5, PM10, CO₂, NOx, SOx, NHx, temperature, humidity, and traffic-related information. A DQN agent dynamically selects sensing and communication actions using nine environmental and contextual state variables. A customized reward function balances air quality conditions, energy consumption, communication costs, and monitoring requirements. Experimental data were collected through an IoT platform and stored in Supabase. The agent was trained using 103 valid observations over 200 episodes and independently evaluated on 114 observations. Training rewards increased from −43.62 to approximately 270 after convergence. Evaluation achieved a total reward of 316.092, an average reward of 2.773 per decision step, and an average energy cost of 0.20 per step. Under stable environmental conditions, the agent consistently selected SLOW_SAMPLE, reducing unnecessary sensing operations. These findings demonstrate the feasibility of DQN-based adaptive monitoring and provide a scalable foundation for energy-efficient, self-optimizing IoT environmental sensing systems under varying environmental conditions.

DESIGN AND DEVELOPMENT OF A LOCATION-AWARE WEB-BASED BOARDING HOUSE SEARCH AND BOOKING SYSTEM USING EXTREME PROGRAMMING Muhammad Arif Furqon; Sudewi Sudewi
IJISCS (International Journal of Information System and Computer Science) Vol 9, No 1 (2025): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v9i1.1920

The increasing demand for affordable and accessible boarding houses among students and workers highlights the need for efficient digital accommodation services. Conventional boarding house searches often involve limited information, manual visits, and difficulties in comparing rental prices, facilities, and locations. This study aims to design and develop a mobile-responsive web-based boarding house information and booking system in Pringsewu, Indonesia, integrating accommodation categorization, online reservations, and location-based search functionality. The system was developed using the Extreme Programming (XP) methodology, supported by Unified Modeling Language (UML) diagrams and a MySQL database. Data requirements were identified through observations, interviews, and literature reviews involving prospective tenants and boarding house owners. The proposed system incorporates six primary interfaces: homepage, boarding house categories for male and female tenants, accommodation listings, property details, online booking, and geographical location visualization. Location-based features provide information on boarding house proximity to Pringsewu City Center, enabling users to evaluate accommodation accessibility. The resulting system design demonstrates an integrated approach to improving accommodation information accessibility, simplifying reservation workflows, and supporting digital property promotion. The proposed platform provides a foundation for user-centered boarding house management and future evaluation of usability, functionality, and booking efficiency.

DISEASE PATTERN DISCOVERY USING K-MEANS CLUSTERING FOR DATA-DRIVEN HEALTHCARE DECISION SUPPORT Echa Febrinasari; Moh. Zainal bin Noor Sulaiman
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 2 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i2.1916

The increasing availability of electronic healthcare records creates opportunities to discover disease patterns and support evidence-based clinical management. This study aims to identify disease patterns among patients enrolled in Indonesia's National Health Insurance (BPJS) program using K-Means clustering and examine their potential contribution to data-driven healthcare decision support at Bandung Mitra Insani Clinic. A quantitative data mining approach was employed following the Knowledge Discovery in Databases (KDD) framework, encompassing data selection, preprocessing, transformation, clustering, and evaluation. Patient age, gender, and disease diagnosis were analyzed using the K-Means algorithm implemented in Orange Data Mining. The clustering process identified two distinct patient groups with different demographic and clinical characteristics. The first cluster predominantly comprised younger patients diagnosed with common acute conditions, including dyspepsia, gastritis, respiratory infections, and migraine. Conversely, the second cluster primarily represented older patients with chronic conditions, particularly hypertension and diabetes mellitus, indicating potentially greater needs for continuous monitoring and long-term care. Cluster quality assessment using the Silhouette Coefficient yielded values ranging from 0.55 to 0.71, suggesting moderate to relatively strong cluster separation. Scatter plots and box plots further facilitated the interpretation of patient distributions and disease characteristics. These findings demonstrate the potential of unsupervised learning to transform routine healthcare records into actionable insights for identifying disease patterns, prioritizing healthcare services, anticipating resource requirements, and informing preventive interventions. The proposed approach provides an analytical foundation for data-driven healthcare decision support in primary care settings, although further validation is required to establish its generalizability and clinical utility

Page 13 of 15 | Total Record : 141

11 12 13 14 15

Filter by Year

2017 2026

Filter By Issues

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Muhamad Muslihudin

Contact Email
ijiscs@ftikomibn.ac.id

Phone
+6272922240

Journal Mail Official
ijiscs@ftikomibn.ac.id

Editorial Address
Editor IJISCS (International Journal of Information System and Computer Science) Bakti Nusantara Institute Street Wisma Rini No.09 Pringsewu, Lampung Phone: 0729-22240

Location
Kab. pringsewu,

Lampung

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Muhamad Muslihudin

Contact Email ijiscs@ftikomibn.ac.id

Phone +6272922240

Journal Mail Official ijiscs@ftikomibn.ac.id

Editorial Address Editor IJISCS (International Journal of Information System and Computer Science) Bakti Nusantara Institute Street Wisma Rini No.09 Pringsewu, Lampung Phone: 0729-22240

Location Kab. pringsewu, Lampung INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Muhamad Muslihudin

Contact Email
ijiscs@ftikomibn.ac.id

Phone
+6272922240

Journal Mail Official
ijiscs@ftikomibn.ac.id

Editorial Address
Editor IJISCS (International Journal of Information System and Computer Science) Bakti Nusantara Institute Street Wisma Rini No.09 Pringsewu, Lampung Phone: 0729-22240

Location
Kab. pringsewu,

Lampung

INDONESIA