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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing International Journal of Informatics, Economics, Management and Science
Simanjuntak, Dita Madonna
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Library & Information Science Materials Science & Nanotechnology Neuroscience Physics

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Machine Learning for Securing API Gateways : a Systematic Literature Review Hutagaol, B. Junedi; Sitorus, Riama Santy; Simanjuntak, Dita Madonna
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6788

Abstract

The rapid growth of mobile banking has improved access to financial services but also introduced heightened cybersecurity risks, particularly due to vulnerabilities in API Gateways and limited user awareness of cyber threats. This study conducts a Systematic Literature Review (SLR) to explore how machine learning (ML) can address both technical and human-centric security challenges in digital banking. By reviewing sixteen peer-reviewed studies published between 2019 and 2025, the study identifies key ML techniques such as anomaly detection, behavior-based models, and deep learning architectures that are effective in detecting and mitigating API-based attacks. In parallel, the review examines ML applications aimed at enhancing user cybersecurity awareness, including personalized alert systems, user segmentation, and adaptive education mechanisms. Thematic synthesis reveals several challenges, including data availability and privacy, the interpretability of complex models, and integration with existing banking infrastructures. However, the study also highlights significant opportunities, such as the use of federated learning to preserve privacy, explainable AI to improve trust, and dynamic alert systems to prevent user fatigue. Based on the synthesis, a conceptual architecture is proposed to integrate ML-driven API threat detection and user education within mobile banking platforms. The findings provide valuable insights for both academic research and practical implementation, contributing to the development of intelligent, user-aware cybersecurity frameworks in the financial sector.Keywords: API Gateway Security, Cybersecurity Awareness, Machine Learning, Mobile Banking, Systematic Literature Review.
Implementation of a Web-Based New Student Admissions Application (PPDB) at the Al-Kautsar Mauk Islamic Boarding School Sugiyono, Sugiyono; Kristiyanto, Yogi; Radhiah, Ainatul; Simanjuntak, Dita Madonna
International Journal of Informatics, Economics, Management and Science Vol 4 No 2 (2025): IJIEMS (August 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v4i2.2040

Abstract

The manual new student admissions (PPDB) process in Islamic boarding schools creates various obstacles such as time inefficiency, data input errors, and the risk of archive loss. This study aims to design and implement a web-based digital new student registration system at the Al-Kautsar Mauk Tahfidzul Qur'an Islamic Boarding School. The method used is software engineering with a Waterfall model approach, starting from needs analysis, design, development, and evaluation. The results show that the system can speed up the form filling process from 10–15 minutes to 2–3 minutes per participant, as well as improve the accuracy and security of data storage through the integration of Google Apps Script and Google Spreadsheets. The system allows admins to access and filter data in real-time without manual re-input. Trials were conducted through simulations with 10 participants and training was provided to admins to ensure smooth implementation. In conclusion, this web-based student admissions (PPDB) system has a positive impact on the efficiency, transparency, and readiness of Islamic boarding schools in facing the digitalization of educational administration.
Capability-Based API Gateway Technology Selection Analysis for Banking Cybersecurity Solution Using AHP Method Sitorus, Riama Santy; Hutagaol, B Junedi; Simanjuntak, Dita Madonna
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14328

Abstract

The growing reliance on APIs in the banking sector, driven by digital transformation, necessitates robust API Gateways that balance performance with strong security measures to address risks like API abuse, man-in-the-middle attacks, and data scraping, while ensuring compliance with regulations such as PCI-DSS, GDPR, and OJK standards. This study bridges the gap in technical guidance by developing a comprehensive evaluation framework using the Analytic Hierarchy Process (AHP) to determine the most suitable API Gateway for banking. The findings identify Apigee as the optimal choice, scoring 1.4277 for its superior authentication, traffic encryption, threat detection, deployment flexibility, cloud integration, and API management. IBM API Connect, scoring 0.6186, is a strong alternative with excellent security and management features but limited scalability and deployment flexibility. Kong and Axway API Gateway follow with scores of 0.4215 and 0.4627, excelling in deployment and integration but lacking critical security features for banking. This research emphasizes the strategic importance of selecting the right API Gateway to bolster cybersecurity and API management in banking, recommending Apigee as the primary solution and IBM API Connect for complex IT infrastructures. It also contributes to the literature by providing a structured, quantitative approach to API Gateway selection and suggests future research exploring AI integration, advanced analytics, and cost-benefit analyses for informed decision-making in the financial sector.
Co-Authors Hutagaol, B Junedi Hutagaol, B. Junedi Kristiyanto, Yogi Radhiah, Ainatul Sitorus, Riama Santy Sugiyono Sugiyono