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All Journal Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Ilmu Komputer dan Sistem Informasi
Baringin Sianipar
Universitas HKBP Nommensen
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Library & Information Science Mechanical Engineering

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A Comparative Performance Evaluation of Unsupervised Learning Algorithms for Clustering Stunting Prevalence in Aceh Province Novia Hasdyna; Rozzi Kesuma Dinata; Baringin Sianipar
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.27009

Abstract

Stunting remains a significant public health issue in Indonesia, particularly in Aceh Province, where considerable disparities continue to exist across districts and municipalities. Identifying regional prevalence patterns is crucial for developing evidence-based intervention strategies. This study assesses the performance of four unsupervised learning algorithms, namely K-Means, Hierarchical Clustering, Gaussian Mixture Model (GMM), and Fuzzy C-Means (FCM), for clustering district-level stunting data in Aceh Province across five observation periods. Algorithm performance was evaluated using the Calinski-Harabasz Index, convergence efficiency, and cluster interpretability. The findings demonstrate that Fuzzy C-Means outperformed the other methods, achieving the highest Calinski-Harabasz score of 49.75, followed by GMM with 42.61, Hierarchical Clustering with 36.48, and K-Means with 25.30. In addition, FCM showed the fastest convergence, requiring only three iterations. Three stable regional clusters were identified, representing high, moderate, and low prevalence levels. High-prevalence areas included Aceh Barat, Aceh Utara, Aceh Tenggara, Pidie Jaya, Aceh Barat Daya, Simeulue, and Bener Meriah, whereas Subulussalam constituted the low-prevalence cluster. These findings indicate that Fuzzy C-Means provides a reliable approach for regional stunting classification and may contribute to more targeted policy interventions in Aceh Province.
Hardening Keamanan Server eOffice Apache dengan TLS 1.3 dan Fail2ban Parulian Parulian; Baringin Sianipar; Danny Sihombing
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.348

Abstract

The security of campus digital services has become increasingly critical due to the rising intensity of automated attacks such as brute-force attempts, vulnerability scanning, and file upload exploitation targeting web-based administrative systems. The eOffice server of Universitas HKBP Nommensen, which serves as the central platform for document management and official correspondence, is also exposed to such threats. This study aims to enhance server security by implementing a defense-in-depth hardening strategy on Apache 2.4. The methodology includes the activation of TLS 1.3 for modern encrypted communication, the implementation of OWASP-compliant security headers, directory isolation to restrict malicious file execution, and the deployment of Fail2ban as a log-based Intrusion Prevention System (IPS) using a multi-jail approach. Evaluation was conducted using SSL Labs, SecurityHeaders.com, and attack log analysis. The results demonstrate significant improvements, highlighted by an upgrade in SSL rating from grade B to A+ and an increase in Security Headers rating to Grade A. In addition, the implemented IPS proved effective in detecting and mitigating automated attacks in real time. In conclusion, the combination of Apache hardening, modern TLS configuration, and log-based intrusion prevention significantly enhances the resilience of eOffice services and can be readily replicated by other institutions with limited resources.
Co-Authors Danny Sihombing Parulian Parulian Rozzi Kesuma Dinata