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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Applied Information System and Management Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Electronics, Electromedical Engineering, and Medical Informatics International Journal of Advances in Data and Information Systems Jurnal Teknik Informatika (JUTIF) International Journal of Electronics and Communications Systems Journal of Computing Theories and Applications Jurnal Informatika Polinema (JIP) Scientific Journal of Informatics Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Setyo Wahyu Saputro
Lambung Mangkurat University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology

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Journal : telematika

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Performance Analysis of the Fuzzing Method in Detecting API Vulnerabilities in Mobile Healthcare Application X Based on OWASP API Security Top 10 Muhammad Ikhwanul Hakim; Radityo Adi Nugroho; Dodon Turianto Nugrahadi; Rudy Herteno; Setyo Wahyu Saputro
Telematika Vol 19, No 1: February (2026)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v19i1.3149

Abstract

Traditional perimeter security measures, such as Web Application Firewalls (WAFs) and static analysis, often fail to detect logic-based vulnerabilities in healthcare Application Programming Interfaces (APIs), creating significant risks for patient data confidentiality. Addressing the scarcity of empirical performance evaluations in this domain, this study employs a grey-box controlled experimental design to assess the effectiveness of automated HTTP fuzzing against a production-grade mobile health application ("Application X"). Using the FFUF tool configured with sequential identifier injection, status-code filtering, and hidden-field probing, the experiment tested 33 endpoints against the OWASP API Security Top 10 2023 benchmarks. To ensure data reliability, a rigorous multi-step validation protocol including replay testing and environmental noise elimination was applied to filter false positives. The results identified 88 distinct vulnerabilities distributed across six categories, with a critical dominance of Security Misconfiguration (API8) and Broken Object Property Level Authorization (API3). Analytically, the high prevalence of API3 reveals a systemic failure in backend serialization, where sensitive fields  including password hashes and internal administrative flags were exposed due to the absence of Data Transfer Objects (DTOs), contradicting the assumption of secure client-side filtering. Limitations of this study include the restriction to a single patient-role perspective and the exclusion of third-party integrations. The study concludes that automated fuzzing is superior to static analysis in detecting runtime data leakage and recommends mandatory Server-Side Output Filtering through explicit DTOs as a critical standard for secure health API development and data privacy compliance.
Functional Evaluation of the Logia Dashboard Using Boundary Value Testing and Cause-Effect Graph Techniques Muhammad Rizky Aulia Ramadhan; Friska Abadi; Dodon Turianto Nugrahadi; Setyo Wahyu Saputro; Rudy Herteno
Telematika Vol 18, No 2: August (2025)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v18i2.3121

Abstract

The Logia Dashboard is a web-based information system used to manage rehabilitation plant data on post-mining land. As an alpha-stage system, Logia requires thorough functional and performance evaluation to ensure that all input validations, logical processes, and system responses operate correctly before wider implementation. This study aims to evaluate the functional reliability and performance of the Logia Dashboard by applying a combined approach of Boundary Value Testing (BVT) and Cause-Effect Graph (CEG) techniques, supported by performance testing using Google Lighthouse. The research design adopts a black-box testing approach. BVT is applied to validate input boundaries on critical features, including login, data editing, QR code generation, and account creation. Meanwhile, CEG is used to model logical relationships between input conditions and system outputs to generate systematic test cases. A total of 39 optimized functional test cases were executed in a controlled local environment. Performance testing was conducted using Lighthouse by measuring key metrics such as First Contentful Paint (FCP), Largest Contentful Paint (LCP), Total Blocking Time (TBT), and Cumulative Layout Shift (CLS). The functional testing results show that 37 out of 39 test cases passed, yielding a success rate of 94.87%. Two failed cases were identified in the login feature, indicating weaknesses in input validation feedback. Performance testing produced an average Lighthouse score of 97, demonstrating that the system has excellent load speed and interface stability, although minor layout instability was detected on certain pages. These results indicate that the combined application of BVT and CEG is effective for detecting boundary-related and logical input errors in alpha-stage web systems. The findings also provide concrete recommendations for improving login validation and interface stability, supporting further development of the Logia Dashboard toward a more reliable and robust system for post-mining land management.
Comparative Analysis of Distance Metrics in KNN and SMOTE Algorithms for Software Defect Prediction Khusnul Rahmi Maulidha; Mohammad Reza Faisal; Setyo Wahyu Saputro; Friska Abadi; Dodon Turianto Nugrahadi; Puput Dani Prasetyo Adi; Hariyady Hariyady
Telematika Vol 18, No 1: February (2025)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v18i1.3008

Abstract

As the complexity and scale of projects increase, new challenges arise related to handling software defects. One solution uses machine learning-based software defect prediction techniques, such as the K-Nearest Neighbors (KNN) algorithm. However, KNN’s performance can be hindered by the majority vote mechanism and the distance/similarity metric choice, especially when applied to imbalanced datasets. This research compares the effectiveness of Euclidean, Hamming, Cosine, and Canberra distance metrics on KNN performance, both before and after the application of SMOTE (Synthetic Minority Over-sampling Technique). Results show significant improvements in the AUC and F-1 measure values across various datasets after the SMOTE application. Following the SMOTE application, Euclidean distance produced an AUC of 0.7752 and an F1 of 0.7311 for the EQ dataset. With Canberra distance and SMOTE, the JDT dataset produced an AUC of 0.7707 and an F-1 of 0.6342. The LC dataset improved to 0.6752 and 0.3733 in tandem with the ML dataset, which climbed to 0.6845 and 0.4261 with Canberra distance. Lastly, after using SMOTE, the PDE dataset improved to 0.6580 and 0.3957 with Canberra distance. The findings confirm that SMOTE, combined with suitable distance metrics, significantly boosts KNN’s prediction accuracy, with a P-value of 0.0001.
Co-Authors Akhmad Zakirin Akhtar, Zarif Bin Andi Farmadi Andi Farmadi Andi Farmadi Angga Maulana Akbar Anshory, Muhammad Naufal Badali, Rahmat Amin Deni Sutaji Deni Sutaji Dodon Turianto Nugrahadi Dwi Kartini, Dwi Elvina Nur Hana Fadhillah, Muhammad Alif Fatma Indriani Fatma Indriani Febrian, Muhamad Michael Friska Abadi Friska Abadi Hanafi, Muhammad Bashir Hariyady Hariyady Herteno, Rudy Hertono, Rudy Irwan Budiman Irwan Budiman Kamil, Hawariul Kenji Satou Khusnul Rahmi Maulidha Martalisa, Asri Maulana Abdul Rahman Mbeledogu, Njideka Nkemdilim Mohammad Reza Faisal Muhammad Faza Azhiman Saputra Muhammad Fikri Muhammad Helmi Muhammad Ikhwanul Hakim Muhammad Itqan Mazdadi Muhammad Khalid Maulana Muhammad Nazar Gunawan Muhammad Noor Muhammad Reza Faisal, Muhammad Reza Muhammad Rizky Aulia Ramadhan Muliadi Nabella, Putri Nur Hidayatullah, Wildan Puput Dani Prasetyo Adi Putri Nabella Radityo Adi Nugroho Radityo Adi Nugroho Rahmat Budianoor Rahmayanti Rahmayanti Rahmina Ulfah Aflaha Raidra Zeniananto Ramadhan, As'ary Reza Faisal, Mohammad Rezeki, Abdillah Rozaq, Hasri Akbar Awal Rudy Herteno Rudy Herteno Rudy Herteno Rudy Herteno Saragih, Triando Hamonangan Suryadi, Mulia Kevin Syahputra, Muhammad Reza Syarif Maulana, Syarif Triando Hamonangan Saragih Ujang Ruyandi Wahyudi Ariannor Wardana, Muhammad Difha YILDIZ, Oktay Yulia Yudihartanti