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International Journal Software Engineering and Computer Science (IJSECS)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : 27764869     EISSN : 27763242     DOI : https://doi.org/10.35870/ijsecs
Core Subject : Science,
Computer Science & IT
IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer science. IJSECS is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information technology and computer science applications..
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 387 Documents
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IoT-Based Prototype System for Automated Measurement of Human Height, Body Weight, and Temperature Using Sensors Christian P. Colombini; Frencis M. Sarimole
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5202

Abstract

This study presents the development of an IoT-based prototype for automatic measurement of body height, weight, and temperature using Arduino Uno microcontroller. The research responds to operational challenges observed at Puskesmas Cengkareng Timur, where conventional manual measurement tools contribute to process inefficiencies and frequent data recording errors during patient examinations. The prototype integrates three sensor components: HC-SR04 ultrasonic sensor for height measurement, Load Cell with HX711 amplifier module for weight detection, and MLX90614 infrared sensor for contactless temperature monitoring. Sensor outputs are processed through Arduino Uno and displayed via I2C LCD interface. Performance evaluation through laboratory calibration and field trials indicates measurement accuracy within 0.15% error margin across all parameters. Implementation of this device at the health center demonstrates potential for improving service delivery efficiency and reducing patient queue duration during preliminary health screening
Design of Recapitulation System Pending Inpatient Claims to Enhance BPJS Verification Efficiency Using Extreme Programming Belinda Nuryania Prameswari; Falaah Abdussalaam; Yuyun Yunengsih
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5229

Abstract

This study designs and develops an information system with a centralized database for recapitulating pending inpatient claims at Hospital X Bandung. The system assists casemix officers in optimizing report accuracy, analyzing frequent ineligible claim types, and minimizing recurrent case probability. Hospital X currently employs a conventional Excel-based process lacking centralized analytics for case classification and periodic data management. The research methodology employs Extreme Programming (XP), selected for its rapid iteration cycles, flexibility, and continual improvement capabilities. Data collection combines direct observations, structured interviews with four medical record installation officers, and systematic literature review. The XP approach enables iterative development with continuous user feedback, ensuring the system meets operational requirements. Implementation results demonstrate measurable improvements: processing time decreased by 35%, pending claim rates reduced by 40%, and classification accuracy increased by 75%. The system architecture comprises four modules: data entry, claim case classification, report generation, and dashboard visualization. Each module underwent rigorous testing through Black Box Testing methodology, validating functionality and user experience. Current system constraints include absence of INA-CBGs system integration, advanced data encryption protocols, and cross-network usage capabilities. The standalone desktop architecture limits simultaneous multi-user access. Despite these constraints, the system successfully simplifies recapitulation workflows and establishes a foundation for future development, particularly web-based architecture and predictive analytics integration
Decision Tree-Based Classification System for Elderly Social Aid Beneficiaries in Jakarta: Case Study Implementation in RW 13, Malaka Jaya Sub-Distric Sutisna Sutisna; Hermawan Susanto
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5243

Abstract

Social assistance distribution to elderly populations in urban areas, particularly Jakarta, frequently encounters challenges in accurately identifying eligible recipients. The present study develops a classification model for elderly social assistance recipients using the Decision Tree algorithm to enhance objectivity and precision in beneficiary selection. Field research was conducted in RW 13, Malaka Jaya Sub-District, East Jakarta, utilizing primary data gathered through systematic observation. Key variables including age, income level, residential ownership status, health conditions, and family dependents were incorporated into the classification framework. The CRISP-DM methodology structured the analytical process, spanning from initial data exploration through model validation. Model testing employed a 70:30 data partition strategy, achieving 95.84% classification accuracy. Findings demonstrate the model's capability in determining eligibility for Jakarta's elderly social assistance program. Implementation of the proposed classification system promises to strengthen transparency, improve targeting precision, and establish evidence-based decision-making in social welfare distribution.
Designing an Early Warning Feature in the Grade Management Information System to Support Academic Performance Monitoring Seliwati Seliwati; Al Razaq Al Razaq
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5268

Abstract

An automated early warning mechanism for monitoring student academic achievement has been designed and deployed, seamlessly integrated within a higher education institution's academic information platform. The mechanism assists students in maintaining consistent performance while enabling preventive intervention when grade deterioration occurs. Development followed the Spiral Model, emphasizing iterative refinement, risk analysis, and continuous adaptation based on user feedback. Final grades derive from weighted assessment categories: participation, assignments, mid-term examinations, and final examinations. When a student's course grade falls to ≤60, automated warning notifications appear instantly on their dashboard. Implementation leveraged PHP with the Laravel framework, MySQL databases, and Visual Studio Code as the development environment. Data sources included campus academic records, user interviews, and notification logs. Evaluation employed Black Box Testing incorporating Equivalence Partitioning and Boundary Value Analysis techniques. Findings demonstrate that the notification mechanism operated with high accuracy and received positive user reception, suggesting strong potential for enhancing student awareness, promoting self-reflection, and facilitating timely academic improvement
Application of Geographic Information System (GIS) in PT Pesona Khatulistiwa Nusantara Community Empowerment Initiatives Fitri Fitri; Seliwati Seliwati
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5316

Abstract

PT Pesona Khatulistiwa Nusantara (PT PKN) has implemented a Geographic Information System (GIS) to advance its Community Development and Empowerment Program (PPM) and strengthen Corporate Social Responsibility (CSR) practices in pursuit of sustainable development. The system facilitates interactive mapping, spatial data administration, and digital dissemination of PPM activities across education, health, economic, and environmental sectors. The research adopts a qualitative approach combined with Agile development methodology, executed through four sprints between February and May 2025. Development stages encompass user requirement identification, interface design, system construction using Laravel and Leaflet.js, and phased testing through functional and acceptance trials. Eight location points and four program categories were successfully mapped, with usability testing involving ten users yielding favorable outcomes regarding system performance and user experience. Results indicate that GIS integration decreased average information retrieval time from nine minutes (manual reports) to under three minutes while expanding public access to program data. The PPM GIS strengthens transparency, enables participatory monitoring, and supports evidence-based program planning aligned with community needs
Improving the UI/UX Design Quality of the Informatics Engineering Study Program Website at Universitas Bina Darma Using the Design Thinking Method Kiagus Fallah Abrar Al Karim; Devi Udariansyah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5337

Abstract

Rapid advances in information technology have transformed multiple sectors, particularly education, where digital platforms play an increasingly vital role in academic operations. Study program websites now serve as primary channels for information dissemination and communication between institutions and their stakeholders. Yet the Informatics Engineering Study Program website at Universitas Bina Darma faces notable usability problems affecting both interface design and user experience quality. A heuristic evaluation survey of 100 students identified several critical issues: absent active menu indicators that hinder navigation tracking, unattractive visual layouts that reduce user engagement, and ambiguous icons and terminology that create confusion during interaction. To address these challenges, researchers employed the Design Thinking framework—a user-centered methodology that emphasizes empathy, ideation, and iterative testing. The framework guided the development of a redesigned prototype, which underwent rigorous evaluation through the Maze platform across four distinct user task scenarios covering key website functions. Test outcomes demonstrated 100% task completion rates among participants, with an average usability score of 89, placing the design in the excellent category. The redesigned interface delivers substantially improved user experience through enhanced navigation clarity, better visual hierarchy, and more intuitive interaction patterns. These improvements establish a solid groundwork for continued development and eventual implementation of systems, offering practical solutions that can be adapted for similar academic website redesign projects.
Application of Extreme Programming Methodology in the Development of a Web-Based Mortality Reporting System with the Laravel Framework Iin Inarotul Huda; Yuyun Yunengsih; Falaah Abdussalaam
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5354

Abstract

Hospital mortality data management directly influences service quality and strategic decision-making capabilities. While electronic medical records have become standard practice in healthcare facilities, existing systems frequently lack the adaptive features necessary for efficient mortality reporting. We address these limitations through the development of a web-based mortality reporting system using Extreme Programming (XP) methodology and the Laravel Framework. The development process engaged two primary user groups: nurses responsible for data entry and medical record officers managing validation and reporting. Black-box testing validated system functionality against operational requirements. Performance evaluation revealed substantial operational gains: patient data entry time decreased from 7-10 minutes to 2-3 minutes, duplicate validation transitioned from manual verification to automated real-time checking, and quarterly report generation reduced from 2-3 hours to 10-20 seconds. The XP methodology, particularly pair programming practices, accelerated defect resolution and enhanced system responsiveness to user feedback. These results demonstrate that iterative development approaches combined with modern web frameworks can fundamentally transform healthcare data management workflows, replacing error-prone manual processes with reliable, efficient digital solutions.
Optimization of Bandwidth Management Using Y.1731 Method Based on Ethernet OAM on Raisecom Devices in Metro Ethernet Networks Muhamad Rafli Alfiansyah; Nandang Sutisna
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5418

Abstract

The growing demand for reliable Quality of Service (QoS) in Metro Ethernet networks has highlighted the need for a bandwidth management approach that is both standardized and efficient. This research explores the optimization of bandwidth configuration through the implementation of the ITU-T Y.1731 protocol, which operates within the framework of Ethernet Operations, Administration, and Maintenance (OAM). A network simulation was carried out using the Enterprise Network Simulation Platform (eNSP) with Huawei devices, serving as a functional equivalent of Raisecom equipment. The study employed a quantitative experimental method, involving the design and configuration of a Metro Ethernet topology, the deployment of Connectivity Fault Management (CFM), and the activation of performance monitoring mechanisms such as Delay Measurement Message (DMM) and Loss Measurement Message (LMM). Key performance indicators analyzed included delay, jitter, and packet loss, observed before and after the Y.1731 implementation. The findings reveal that the application of Y.1731 improved bandwidth utilization efficiency by up to 25%, reduced average delay, minimized jitter, and produced measurable data for validating Service Level Agreement (SLA) compliance. Overall, the integration of Y.1731 into Metro Ethernet networks based on Huawei devices demonstrates a practical and effective solution for strengthening service performance and ensuring network reliability.
Apache Spark for Business and Financial Data Engineering: A Systematic Literature Review Ahmad Bilal Almagribi; Bambang Purnomosidi Dwi Putranto
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5419

Abstract

This paper is an SLR that maps the application of Apache Spark in data engineering in the business and finance domains. Practitioners and researchers alike would find it interesting to know how Apache Spark has been applied to solve big data problems as organizations continue to deal with large volumes of data. By analyzing publications from the Scopus database for 2021-2025, we try to find trends and methodologies currently in use as well as gaps in research existing in the field. It was found that Apache Spark is primarily used for sentiment analysis and trend analysis on social media, particularly Twitter, since its real-time processing capability can help understand market dynamics and consumer behavior. The platform carries out predictive tasks like predicting customer churn or pricing financial assets (stocks, bonds, options), proving its versatility across different business applications. Also, this platform is popular for anomaly detection such as transaction fraud with efficiency and cost being the main drivers of adoption. The landscape is not monolithic since some studies propose alternative platforms indicating that Apache Spark may not be the best option for every scenario. Based on our findings, we suggest future research directions that would push the boundaries of the field: using social media data sources other than Twitter for more general market sentiment, applying more varied algorithms to improve prediction accuracy, and extending Spark's application into new areas like currency exchange rate forecasting, credit risk analysis, Anti-Money Laundering (AML) detection as well as Data Lakehouse architecture implementation. These recommendations are meant to steer researchers toward uncharted territories where significant value could be unlocked for business and finance with the help of Apache Spark.
Deep Learning Based Augmented Reality for 3D Object Recognition Muhamad Ziaul Haq; Nursalim Nursalim
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5431

Abstract

Augmented Reality (AR) technology is being widely adopted in various fields such as education, entertainment, and creativity. However, there are still some challenges to be overcome in recognizing and rendering three-dimensional (3D) objects accurately and in real-time. We implemented an AR system that utilizes deep learning techniques to recognize 3D objects with improved accuracy levels. Our approach involved training a Convolutional Neural Network (CNN) model using 3D object datasets captured from different viewpoints. The development included designing the network architecture, training the model, evaluating its accuracy, and integrating it into an AR platform based on Unity 3D and Vuforia SDK. The results indicated that the system could achieve recognition of the 3D objects with an average accuracy of 93.7%, precision of 92.4%, and recall of 91.8%, all while keeping response times below 0.8 seconds. Objects with complex geometries like cars and chairs had recognition rates above 94%, while those with similar textures had lower accuracy because of detailed surface complexities. It allows stable interactive visualization of objects in augmented reality even under different lighting conditions and camera angles. Combining deep learning with AR improves the quality of object recognition and provides a more realistic interactive experience. This paper discusses the advances made in AR technology toward better adaptability and efficiency, which can be applied to interactive education, industrial simulation, architecture, and medical fields.

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