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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 423 Documents
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Implementation of Android-Based Futsal Court Booking Application Using Flutter (Case Study: Futsal Hayani Kopti, West Cengkareng) Veri Arinal; Mesra Betty Yel; I Komang Dewa Ananda Putra; Fauzan Azima; Mohammad Farhan; Muhammad Ikhsan Hakim; Dadang Mulyana Iskandar; 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 Wahyu Purnama Magribi; Muhammad Fazly Qusyairy; Tino Saputra
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 Jovanka Sabila Pertiwi; Resmi Darni; Yeka Hendriyani; Yulia Fatmi
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 Aldi Juliansyah; Richky Faizal Amir
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 Henoch Juli Christanto
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 Marlina Dama Lero; Ardiyanto Dapadeda; Maria Wilda Malo
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 RaviKumar Bhuvanagiri
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.
Web-Based Information System for Managing Savings and Loans at the Mera Ndi Ate Cooperative Marlince Kadobo; Ardiyanto Dapadeda; Dian Fransiska Ledi
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.v6i1.6675

Abstract

A web-based cooperative information system — accessible at any time via the internet — allows administrators and members to retrieve real-time financial data, automate transaction recording, generate periodic reports, and monitor loan and deposit statuses with measurable accuracy. At the Mera Ndi Ate Cooperative, however, member registration and financial data management are still conducted manually through ledger entries, producing recurring problems: duplicate records, transcription errors, vulnerability to physical data loss, slow reporting cycles, and underutilized computing infrastructure. A web-based system was therefore developed to support daily operations, accelerate service delivery, reduce recording errors, and improve financial transparency. The study adopted a descriptive qualitative approach and applied the Waterfall model as the system development methodology. The resulting Mera Ndi Ate Cooperative Information System covers the full operational cycle — from member registration to financial reporting — and is supported by a real-time dashboard connected to a centralized database that tracks deposits, loans, and installment payments. The system measurably improves data accuracy, access speed, and operational accountability, while also strengthening the cooperative's capacity for long-term financial governance.
Layered Security Model for JWT-Based Authentication and Authorization in Golang Echo REST APIs Giovanni Ekayuda; Suprihadi Suprihadi
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.v6i1.6692

Abstract

Microservices architecture improves scalability and flexibility in modern distributed systems, yet it simultaneously widens the attack surface through decentralized service communication. Many existing implementations rely primarily on token validation without structured service-level authorization enforcement, leaving systems exposed to privilege escalation vulnerabilities. This study designed and evaluated a layered security model for a RESTful Application Programming Interface built with the Go Echo framework. The proposed approach combines JSON Web Token authentication using asymmetric cryptography with a token versioning mechanism, and pairs Role-Based Access Control with Attribute-Based Access Control within a sequential middleware pipeline. The methodology covered system architecture design, middleware implementation, structured security testing, and response time analysis. All simulated unauthorized access scenarios — including vertical and horizontal privilege escalation attempts — were successfully blocked. The average response time under the fully secured configuration measured 24.9 ms, indicating that the overhead introduced by the layered middleware remains practically acceptable. These findings suggest that separating authentication and authorization at the service level produces measurable security gains without meaningfully degrading system performance in microservices-based REST API applications.
Analysis of Gender Inequality in Artificial Intelligence-Based Recruitment Systems: A Systematic Literature Review (SLR) Herdaning Sandra Kumalasari; Magdalena A. Ineke Pakereng
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.v6i1.6746

Abstract

The increasing adoption of Artificial Intelligence (AI) in recruitment has raised concerns about algorithmic discrimination that may disadvantage certain groups, particularly women. This study analyzed gender inequality in AI-based recruitment systems by synthesizing evidence from both technical and ethical perspectives. A Systematic Literature Review (SLR) was conducted on studies published between 2020 and 2025, applying predefined inclusion and exclusion criteria, followed by screening, quality assessment, and thematic synthesis. The review retained 10 studies (n = 10) that met the eligibility and quality threshold. Historically imbalanced training data emerged as the most frequently reported driver of gender bias, often producing unfair screening, ranking, and selection outcomes. Fairness conclusions were found to depend strongly on how recruitment outcomes were defined and measured, and prior studies consistently called for multiple fairness metrics supported by auditing practices. The literature also identified mitigation strategies spanning data balancing, fairness-aware model evaluation, transparency and audit mechanisms, and human oversight in decision-making. Gender bias in AI-based recruitment is, at its core, a socio-technical problem that requires combined interventions across data governance, model evaluation, and organizational accountability, while research gaps remain for future empirical validation and responsible AI deployment.

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