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Muhammad Wali
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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 284 Documents
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Expert System for Disease Diagnosis in Pregnant Women Using Backward Chaining Method Odelia, Yosefin Caltrin; Hasan, Patmawati; Tatuhey, Emy Lenora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4498

Abstract

Healthcare providers treating pregnant women need reliable tools for accurate disease diagnosis. We created an expert system that assists doctors in identifying illnesses during pregnancy through backward chaining inference methods. The project involved collaboration with medical professionals at North Jayapura Health Center who shared their clinical expertise to develop the system. Our backward chaining method examines patient symptoms by working backward from potential diseases to find diagnostic matches. Through detailed interviews, healthcare professionals contributed their years of experience treating pregnant patients. We transformed their knowledge into diagnostic rules that help the system recommend possible diagnoses based on symptom patterns. The system serves as a decision support tool that helps doctors make quicker, more confident diagnostic choices. Many pregnancy-related diseases share similar symptoms, which can confuse even experienced practitioners. Our tool helps sort through these diagnostic challenges while preserving the doctor's authority in making final decisions. Evaluation showed the expert system significantly improved diagnostic performance in primary care settings. Many healthcare facilities lack access to specialists familiar with pregnancy complications. The system brings expert-level diagnostic knowledge to these underserved areas, improving patient care quality
Development and Evaluation of an Expert System for the Early Diagnosis of Dental Diseases Purwanto, Eko; Sari, Devi Pramita; Mohd, Farahwahida
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4500

Abstract

Dental diseases, such as caries, periodontitis, and gingivitis, affect public health worldwide, especially in regions where healthcare access remains restricted. The study develops an expert system for early dental disease diagnosis using Forward Chaining and Certainty Factor methods. The system overcomes deficiencies found in previous approaches, such as Naive Bayes and Dempster-Shafer, which demonstrate insufficient accuracy and unclear result interpretation. The developed expert system incorporates a knowledge base containing 7 diseases, 40 symptoms, and 7 diagnostic rules. Forward Chaining enables inference of potential diagnoses from reported symptoms, while the Certainty Factor evaluates diagnostic reliability by calculating confidence levels. System evaluation through Black Box testing achieved 92% diagnostic accuracy, and usability assessments revealed 85% user satisfaction rates, demonstrating that the system proves reliable, accurate, and accessible. Research findings indicate the expert system offers viable solutions for improving dental disease diagnosis in underserved and remote areas, potentially enhancing oral health outcomes through early detection and prompt intervention.
User Trust, Security, and Data Privacy Awareness in GoPay Usage Using Protection Motivation Theory (PMT) Gitareswara, Diva Ayu; Suratno, Tri; Lestari, Dewi
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4518

Abstract

The widespread adoption of GoPay in Indonesia has raised significant questions about user data privacy and security, dimensions frequently overlooked by traditional utility-focused adoption models such as TAM and UTAUT. This research addresses that gap by applying Protection Motivation Theory (PMT) to examine the psychological drivers behind GoPay usage intention. Through a quantitative national survey of 105 active users analyzed via PLS-SEM, the model explained 69.3% of variance in behavioral intention (R²=0.693). Results show that privacy concern, perceived severity, perceived vulnerability, response cost, response efficacy, and trust significantly and positively influence usage intention. In contrast, security features and user self-efficacy were not significant drivers. The findings demonstrate that users' behavioral intentions are more strongly influenced by their evaluation of potential threats and confidence in the service provider's protective capabilities rather than technical security features or personal competence alone. The study advances understanding of digital payment adoption by revealing that psychological threat assessment processes, rather than technical security perceptions, primarily drive user decisions. GoPay users prioritize the platform's ability to protect them over their own technical skills or general security features. These findings offer practical implications for digital wallet providers seeking to enhance user adoption through targeted trust-building strategies rather than solely focusing on technical security improvements.
Automatic Purchase Order Classification Using SVM in POS System at Skus Mart Lestari, Sri; Nadip, Muhamad Zaeni; Akbar, Yuma; Hidayat, Aditya Zakaria; Aula, Raisah Fajri
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4564

Abstract

In retail business processes, decision-making regarding Purchase Order PO submissions often remains manual and subjective, creating risks that impede procurement efficiency. The study develops an automatic classification model to predict PO approval status using Support Vector Machine SVM algorithm integrated within Point of Sale POS systems. Historical purchase transaction data was obtained from SKUS Mart POS database containing 133 entries, including attributes such as item quantity, purchase price, previous stock levels, and total purchase amounts. The research applies CRISP-DM methodology, encompassing business understanding, data exploration, preprocessing normalization using StandardScaler, model training, evaluation, and deployment phases. The model was trained using linear kernel and validated through holdout technique with 80:20 ratio for training and testing. Test results demonstrate that the SVM model achieves 76.69% accuracy, 82.21% precision, 76.69% recall, and 78.51% F1-score. The model was implemented in a web-based POS system CodeIgniter 3 combined with Python scripts to generate automatic classifications displayed directly in the user interface. Although the model demonstrates adequate performance, the study has not compared its effectiveness against other machine learning algorithms such as Random Forest or K-Nearest Neighbor. These findings establish initial groundwork for machine learning integration to support decision automation in procurement systems.
Implementation of Decision Support System for Seed Award Recipient Student Selection at Madrasah Ibtidaiyah Baiturrahman, Bandung, West Java Azzahra, Salma Latifa; Aula, Raisah Fajri; Putri, Nadiya Herdiana
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4604

Abstract

The selection process for Seed Award recipients at Madrasah Ibtidaiyyah Baiturrahman Bandung encounters challenges related to subjective assessment and perceived inequity. The evaluation system applies uniform criteria across all students from grades 1 to 6 without accounting for developmental differences between grade levels. To address these issues, we designed and implemented a web-based Decision Support System utilizing the VIKOR method. We selected VIKOR for its ability to generate optimal compromise solutions in multi-criteria problems involving conflicting considerations. The DSS employs four primary criteria: Religious Practice 20%, Character 20%, Discipline 20%, and Grade Level 40%, with the latter formulated as a cost criterion to ensure fairness across educational levels. We built the system using Laravel framework and tested it with 17 teachers and 20 students as trial participants. Implementation results demonstrate substantial improvements in selection objectivity, evidenced by increased representation of lower-grade students from grades 1 to 2 as award recipients from 18% to 42%. Furthermore, 94% of teachers reported the system as more objective and user-friendly, 75% of students expressed increased motivation following system deployment, and parental complaints were eliminated previously ranging from 5 to 7 cases per semester. These findings indicate that VIKOR-based DSS successfully establishes fairer, more transparent, and accountable selection processes while enhancing stakeholder confidence in evaluation mechanisms within madrasah environments.
12-Lead Electrocardiograph Calibrator Ma'rufi, Mahmud; Harsoyo, Imam Tri; Setiawan, Florentinus Budi
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4726

Abstract

The research develops and evaluates a 12-lead Electrocardiograph (ECG) calibrator using ESP32 microcontroller technology to enhance calibration precision in clinical environments. Healthcare facilities need accurate ECG signal recording through portable calibration devices that maintain ≤ 5% error tolerance. Previous calibrator designs lack unified integration of complete 12-lead functionality, extensive BPM ranges, and variable amplitude control within single portable units. The methodology incorporates hardware-software development, voltage measurements across three assessment points (charger module, ESP32 output, Nextion LCD), BPM validation at four operational settings, and waveform analysis (normal, square) with amplitude evaluation across multiple sensitivities. Experimental results demonstrate an average total error of 1.2% for BPM and amplitude measurements, maintaining voltage stability within ± 5% tolerance limits. Performance analysis validates device reliability for ECG calibration applications, showing optimal performance with square waveform configurations. The ESP32-based calibrator proves technically viable and clinically safe, providing cost-effective, high-precision alternatives to existing solutions. Future development opportunities include triangular waveform integration, Wi-Fi connectivity for remote operation, and rapid calibration initiation features.
Implementation of Educational Game System Using MDLC with Adobe Animate Application Setiawan, Kiki; Sarikah, Dede
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4727

Abstract

Digital gaming has transformed educational practices across Indonesia, creating new pathways for curriculum delivery through interactive entertainment. Educational games now serve as effective learning tools that capture student attention while building essential skills. The research develops and evaluates a multi-level educational puzzle game using Adobe Animate 2022, targeting cognitive skill enhancement and problem-solving abilities across different age groups. Development followed the Multimedia Development Life Cycle (MDLC) approach through six phases: conceptualization, design planning, resource gathering, system building, testing procedures, and final deployment. The puzzle application includes three difficulty levels with varying complexity parameters. Adobe Animate 2022 handled vector graphics creation, interactive programming, and multi-platform publishing. User evaluation involved testing across target demographics to assess usability and learning effectiveness. The finished application successfully demonstrates structured game development using MDLC principles. Testing showed positive user responses with balanced difficulty progression and completion rates that indicate effective entertainment-education integration. The development process provided organized workflows that supported quality control and user satisfaction goals. Adobe Animate 2022 proved capable for educational game creation, enabling smooth asset management and publishing operations. The study establishes a reproducible model for future educational gaming projects while validating game-based learning methods in Indonesian educational settings. Findings suggest that systematic development approaches produce superior educational outcomes compared to informal development practices.
Redesign of The Digital Population Identity Application (DPIA) Interface Using Design Thinking to Improve User Experience Akhsin, Muhammad Zaki Robbi; Irianto, Kurniawan Dwi
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4745

Abstract

The objective of the study is to enhance user experience within the Digital Population Identity Application (DPIA), known as Identitas Kependudukan Digital (IKD), through interface redesign for public administration services in Indonesia. The research employs a user-centered design methodology structured around five sequential phases: user experience analysis, challenge identification, solution ideation, prototype development, and evaluation testing. Data collection involves user interviews and direct observation of application usage patterns. The application prototype underwent redesign based on identified challenges and was subsequently evaluated through quantitative survey methods focusing on usability metrics. Post-redesign testing revealed substantial improvements in ease of use, navigation efficiency, and user comfort levels. The study outcomes aim to advance user-friendly public service applications and may serve as a framework for developing additional digital systems requiring direct community-government interaction.
Mosque Parking System: An Implementation Using Camera and IoT Gahara, Lalu Ahmad Naufal Gina; Irianto, Kurniawan D.
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4856

Abstract

The rapid technological advancement has transformed various aspects of daily life, including parking management in mosque environments. Mosque parking administration often proves inefficient, particularly during religious holidays, leading to vehicle congestion, disorganized parking arrangements, and worshiper delays. This research develops an Internet of Things-based parking capacity calculation system using ESP32-CAM cameras that automatically detect vehicles. The system displays real-time information through a 20x4 I2C LCD and website interface, showing vehicle count, available slots, status (entry/exit), and timestamp data, with storage capabilities in Firebase. Designed using a Human-Centered Design approach, the system was implemented at Darussalam Ganjuran Mosque parking area and evaluated through black box testing. Results revealed 66.67% detection accuracy, successful real-time parking capacity information display, and effective vehicle history storage. Performance limitations included reduced accuracy in low lighting conditions, difficulty tracking high-speed vehicles, and camera resolution constraints. The system allows users to access current parking conditions while enabling mosque administrators to monitor parking areas efficiently.
Smart Door Lock System: A Mobile Application Development Based on IoT Technology Hanifullah, Muhammad A.; Irianto, Kurniawan D.
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4898

Abstract

The research introduces a miniature IoT-based smart door lock system paired with a custom Android application called Jenaela. The system tackles security vulnerabilities inherent in conventional pin tumbler locks, which remain susceptible to lock-picking techniques and provide restricted access control capabilities. The hardware architecture incorporates an ESP32 DOIT V1 microcontroller, PN532 NFC module, relay with optocoupler integration, DC-to-DC step-up converter, and 12V solenoid lock. The software solution features Jenaela, developed using TypeScript and React Native framework, deployed through Expo toolkit and EAS Build Preview. Rather than relying on third-party platforms like Blynk, Jenaela delivers complete customization and superior control mechanisms. Core functionalities encompass user authentication, RFID tag registration and deletion, LAN-based device discovery, and unlocking through both RFID and remote switch methods. Functional testing via Black Box methodology verified proper operation of all features. RFID unlocking demonstrated faster response times compared to WAN-based unlocking due to reduced system dependencies. Results validate the practicality and effectiveness of integrating IoT hardware with custom mobile applications to enhance security through dual access methods and real-time database interaction.

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