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Muhammad Wali
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muhammadwali@amikindonesia.ac.id
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ijsecs@lembagakita.org
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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 29 Documents
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Search results for , issue "Vol. 6 No. 1 (2026): APRIL 2026" : 29 Documents clear
Expert System for Identifying Hardware Damage Using Naïve Bayes Method (Case Study: Computer Laboratory of Sepuluh Nopember University Papua) Sabra, Isaac Samon; Sutejo, Heru; Kungkung, Ajenkris Yanto
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.5400

Abstract

This research aims to design and implement an expert system based on the Naïve Bayes method to identify computer hardware failures in the Computer Laboratory of Universitas Sepuluh Nopember Papua. The laboratory operates approximately 40 computer units used daily by students across multiple study programs, yet is supported by only three technicians — a gap that frequently delays repairs and disrupts practical sessions. The system draws on a knowledge base covering 15 hardware failure categories and 11 observable symptoms, including failures in processors, memory/RAM, storage devices (HDD/SSD), and peripheral components such as keyboards, mice, and monitors. Development followed the Waterfall model, system design was documented using UML, the application was built with CodeIgniter, and evaluation was conducted through accuracy testing against expert diagnoses. Testing on 20 cases yielded a 75% accuracy rate, demonstrating that the system is capable of supporting technicians in accelerating the troubleshooting process, reducing dependence on manual inspection, and sustaining the quality of laboratory practice sessions for students
AutoClusterAPI: A Lightweight Backend Framework for Automated Unsupervised Clustering Pipelines Yunhasnawa, Yoppy; Windawati, Atif; Aldila Cinderatama, Toga; Abdullah, Moch. Zawaruddin; Nur Hamdana, Elok
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.5997

Abstract

This study presents AutoClusterAPI, a lightweight and extensible backend system designed to simplify and accelerate unsupervised clustering workflows. The system addresses a recurring problem in data analysis practice: many practitioners need rapid clustering capabilities but lack the programming or statistical background required to build complete pipelines from scratch. AutoClusterAPI provides an automated, endpoint-driven solution that allows users to perform every stage of clustering — from data loading and cleaning to feature preparation, algorithm execution, profiling, and visualization — through standard HTTP requests. The system is built using Python and the FastAPI web framework, supports eight clustering algorithms, and includes automated preprocessing alongside PCA-based visualization. Functional testing confirms that all endpoints behave correctly under both valid and invalid inputs, establishing the reliability of the system. A case study using a customer segmentation dataset further demonstrates its practical utility, showing that AutoClusterAPI can efficiently generate meaningful cluster structures and interpretable visual outputs. The system offers an accessible yet configurable environment for rapid clustering analysis and establishes a basis for future extensions and real-world deployment.
Preventing Crypto Scams Through Digital Literacy and Cyber Security Maulana, Muhammad Dzaky; Juhana, Agus
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6345

Abstract

Blockchain-based financial technology has reshaped how digital transactions are conducted, yet its rapid adoption has simultaneously expanded the attack surface for a specific class of cybercrime — cryptocurrency fraud. This study examines how digital literacy education and cybersecurity practices, when applied in combination, can reduce the vulnerability of crypto asset holders to scams. A qualitative approach was adopted through a systematic literature review of prior academic studies alongside an evaluation of fraud cases currently documented in Indonesia. The findings indicate that inadequate digital literacy is the primary driver of user susceptibility to online fraud — users who cannot verify token authenticity, assess transaction risks, or identify phishing attempts are structurally exposed. Applying security measures such as two-factor authentication, data encryption, and strong password management demonstrably reduces that exposure by 50–70%. Coordinating digital literacy education, consumer protection regulation, and cybersecurity awareness is necessary to build a safer and more accountable crypto environment. This study is intended to inform the design of educational programs and national policy on digital asset protection within the broader digital economy
Implementation of Android-Based Futsal Court Booking Application Using Flutter (Case Study: Futsal Hayani Kopti, West Cengkareng) Arinal, Veri; Betty Yel, Mesra; Putra, I Komang Dewa Ananda; Azima, Fauzan; Farhan, Mohammad; Hakim, Muhammad Ikhsan; Iskandar, Dadang Mulyana; Sutisna, Sutisna
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6496

Abstract

The rapid development of information technology has encouraged service providers to improve efficiency and service quality, including in futsal court rental services. At Futsal Hayani Kopti Cengkareng Barat, the court booking process is still conducted manually through phone calls or direct visits, which often results in scheduling conflicts, limited access to information, and unstructured data management. These conditions reduce the effectiveness and efficiency of the booking process. This practical work aims to design and implement an Android-based futsal court booking application using the Flutter framework. The developed application provides real-time information on court availability, rental prices, facilities, and online booking features. In addition, the system assists administrators in managing booking schedules and transaction data in a centralized manner. The research method applied is qualitative, employing observation, interviews, documentation, and literature study. System development follows the System Development Life Cycle (SDLC) approach with an internet-based client–server architecture. The implementation results indicate that the application improves booking efficiency, reduces scheduling conflicts, and enhances service quality as well as user satisfaction.
Data Mining for Predicting Creditworthiness in Credit Card Approval: A Systematic Literature Review Purnama Magribi, Wahyu; Fazly Qusyairy, Muhammad; Saputra, Tino
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6618

Abstract

The growing volume of credit card applications has led financial institutions to seek faster and more reliable methods in the approval process. Manual evaluation is not only time-consuming but also susceptible to human error, which can result in poor credit decisions and measurable financial losses. This study conducts a Systematic Literature Review (SLR) to examine data mining techniques applied to creditworthiness prediction. Five research questions were formulated to identify: (1) commonly used data mining techniques, (2) frequently used datasets, (3) performance evaluation metrics, (4) algorithms with the strongest performance, and (5) recurring challenges and practical recommendations. A structured search across three academic databases — Scopus, Google Scholar, and GARUDA — yielded 8 relevant articles (7 primary experimental studies and 1 secondary study) published between 2021 and 2025. The findings show that Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine, and K-Nearest Neighbors are the most widely applied methods. Tree-based algorithms such as Decision Tree and Random Forest consistently yield high accuracy, while K-Nearest Neighbors also delivers strong results in specific experimental settings. Naïve Bayes appears most frequently across studies, and its performance can be improved through metaheuristic approaches such as Particle Swarm Optimization (PSO). Standard evaluation metrics include accuracy, precision, recall, F1-score, and AUC-ROC. The review underscores the importance of data preprocessing, class imbalance handling, and hyperparameter tuning in building reliable prediction models — findings with direct implications for financial institutions seeking to reduce non-performing loan rates.
Design and Development of a Hybrid Rule-Based and Controlled AI Chatbot for Digital Mental Health Services Sabila Pertiwi, Jovanka; Darni, Resmi; Hendriyani, Yeka; Fatmi, Yulia
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.7045

Abstract

Mental health issues have become increasingly prevalent, highlighting the need for accessible and integrated digital psychological services. Existing systems are often fragmented — communication, information delivery, and service management are separated across different platforms, creating operational inefficiencies. This study designs and develops a web-based hybrid chatbot system for digital mental health services at Corporate Psikologi Indonesia. The proposed system applies a hybrid approach combining keyword-based detection, a structured knowledge base, and controlled artificial intelligence to produce consistent and safe responses. A consultation booking feature is built into the same platform to support both informational and service-based interactions. The system was developed using a prototype-based approach and evaluated through functional testing and a preliminary user evaluation in a controlled environment. Results show that the system supports user interaction, delivers relevant mental health information, and facilitates consultation booking and service access effectively. The proposed hybrid chatbot architecture addresses service accessibility while maintaining response reliability. Future work will focus on broader user evaluation and stronger natural language understanding capabilities.
Analysis of Personal Data Security Awareness Level Among Social Media Users Using the Technology Acceptance Model Juliansyah, Aldi; Amir, Richky Faizal
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6554

Abstract

The rapid development of information technology has fundamentally altered communication patterns, most visibly through the widespread adoption of social media as a primary channel for sharing and receiving information. What began as a tool for interpersonal connection has since expanded into a space for commercial activity, personal expression, and mass information exchange — bringing with it a set of risks that deserve more attention than they typically receive. Social media platforms, while offering considerable convenience, carry real threats to personal data security, threats that are too often underestimated by both users and service providers. Personal data routinely spreads across these platforms, sometimes deliberately, more often through carelessness or inattention on either side of the service relationship. The gap between internet penetration rates and actual security awareness among users remains a persistent concern, particularly in developing digital markets where platform adoption has outpaced digital literacy. The present study measured the level of awareness among social media users regarding personal data privacy and security, applying the Technology Acceptance Model (TAM) as the analytical lens. A blended research method was used, combining qualitative and quantitative data collection through a structured questionnaire distributed to 100 randomly selected respondents. The findings indicate a relatively high level of awareness overall: 68.6% of respondents demonstrated awareness of information security practices, while 65.1% showed awareness of personal privacy. These figures are encouraging — though the 15% gap between the two warrants further scrutiny.
Design Recommendations for a Child-Oriented Christian Education App Based on Usability Evidence Christanto, Henoch Juli
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6592

Abstract

Technology has become a routine part of children's learning, including the transmission of religious values through mobile applications. This study evaluates the usability of the Superbook Kids Bible App — a child-oriented Christian learning application — using Nielsen's five usability dimensions: learnability, efficiency, memorability, errors, and satisfaction. A descriptive quantitative survey was conducted with 100 respondents selected through purposive sampling, with sample size determined by Slovin's formula at a 10 percent margin of error. A 25-item questionnaire was validated using Pearson item-total correlations, yielding validity coefficients ranging from 0.598 to 0.824, while reliability testing confirmed good internal consistency. Descriptive results indicate moderate overall usability, with mean scores of 22.40 for learnability, 8.12 for efficiency, 8.65 for memorability, 17.76 for errors, and 14.91 for satisfaction. Category analysis identifies efficiency as the primary bottleneck, with 46 percent of respondents in the low category, followed by learnability at 33 percent, while errors were predominantly moderate at 60 percent. Based on these findings, the study proposes evidence-based design priorities: performance improvements to reduce loading and response delays, streamlined navigation to cut unnecessary steps, and guided onboarding with child-appropriate prompts to support early-stage learnability, alongside clearer feedback and error recovery mechanisms. Future research should combine task-based observation with usage analytics, test interventions such as gamification and personalization, and apply longitudinal designs to examine sustained engagement and learning outcomes in faith-based mobile learning.
Factors Affecting the Effectiveness of CBT Implementation in Student Learning Evaluation Using UTAUT: A Case Study at SMAS Katolik Sint Pieter Waikabubak Lero, Marlina Dama; Dapadeda, Ardiyanto; Malo, Maria Wilda
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6600

Abstract

This study examines the digital transition in the student learning evaluation system at SMA Katolik Sint Pieter Waikabubak through the adoption of a Computer-Based Test (CBT) application. Although CBT has been in use since 2023, persistent issues — including unstable internet connections and limited exam monitoring features — have raised legitimate questions regarding its operational effectiveness. This study aims to evaluate the effectiveness of CBT in student learning assessments and to identify the factors that shape students' behavioral intention to use the system. A quantitative approach grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) was applied. The findings demonstrate that CBT adoption has measurably improved the transparency and accuracy of learning evaluations. Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions each exert a statistically significant effect on students' intention to use CBT, with Perceived Usefulness emerging as the strongest predictor. Age and gender were found to moderate several of these relationships. The results indicate that adequate school infrastructure and an accessible application interface are decisive factors in the success of exam digitization. Schools are advised to continue strengthening their technical and physical support systems to sustain long-term adoption of this technology.
Architecting the Net-Zero Frontier: Systemic Implementation Strategies for Sustainable Infrastructure in the AWS Ecosystem Bhuvanagiri, RaviKumar
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6609

Abstract

Global digital infrastructure in 2026 operates under mounting pressure from climate regulation, tightening energy policy, and growing demands for corporate environmental accountability. Cloud migration is frequently positioned as a straightforward path to sustainability — yet that assumption holds only when customers take deliberate responsibility for what runs inside the cloud. The AWS Shared Responsibility Model makes this obligation explicit: AWS governs the physical layer, while customers own the workload architecture and its carbon consequences. This paper examines how sustainability principles — environmental stewardship, social equity, and economic resilience — can be systematically embedded into AWS IT project delivery. Drawing on empirical data from 2025–2026, we propose a three-layered decision-making model anchored in Silicon-Level Optimization, Geographic Carbon Intensity (GCI), and Temporal Workload Shifting. Each layer addresses a distinct decision horizon, from hardware selection at the design phase through operational lifecycle governance. Projects that adopted this model recorded a 30% reduction in carbon emissions and a 22% decrease in total cost of ownership (TCO), demonstrating that environmental responsibility and financial performance are not competing objectives.

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