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All Journal Journal of Students‘ Research in Computer Science (JSRCS)
Irfan Nugraha
Universitas Kusuma Husada Surakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Analisis Clustering Data Mahasiswa Berdasarkan Nilai Akademik Menggunakan K-Means Muhammad Aliq Aulia; Kresno Ario Tri Wibowo; Irfan Nugraha; Ilham Wahyu Analta
Journal of Students‘ Research in Computer Science Vol. 7 No. 1 (2026): Mei 2026
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/kv0g1g94

Abstract

Academic data in higher education are mainly used for administrative purposes, rather than for meaningful insights. Yet, analyzing student grade data can reveal patterns that help institutions evaluate and improve development strategies. This study grouped student data by academic grades using the K-Means Clustering method. Grades from core courses underwent data collection, preprocessing, cluster number selection, and Clustering using K-Means. The results showed K-Means successfully clustered students by performance level. Each cluster reflected a category of academic ability: high, medium, or low. These results can help institutions monitor progress and design better academic guidance. Thus, applying K-Means may be effective for analyzing student academic data in higher education.
Co-Authors Ilham Wahyu Analta Kresno Ario Tri Wibowo Muhammad Aliq Aulia