Anggreani, Namira
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Pengelompokkan Provinsi Berdasarkan Kelayakan Ruang Kelas dan Tenaga Kependidikan Sekolah Dasar Menggunakan Algoritma K-Means: Analisi Data Periode 2023-2024 Wardani, Maidy Tri; Ramadhani, Varla Octavia; Anggreani, Namira; Sumanto; Kuswanto, Andi Diah
Riau Jurnal Teknik Informatika Vol. 4 No. 2 (2025): Juli 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i2.3389

Abstract

Abstract This study analyzes the disparity in primary education quality across Indonesian regions using K-Means clustering methodology to group 38 provinces based on classroom adequacy indicators and teaching staff availability for the 2023-2024 period. Adopting the CRISP-DM methodology and utilizing datasets from the Ministry of Education, Culture, Research, and Technology, this research reveals significant educational gaps across Indonesian regions. The analysis results show three clusters reflecting educational conditions: Cluster 1 (low category) encompasses 23 provinces (67.6%) dominated by Eastern Indonesia regions such as Papua, Maluku, and other remote areas; Cluster 2 (medium category) consists of 13 provinces (38.2%) including South Sumatra, Riau, and DKI Jakarta; and Cluster 3 (high category) contains only 3 provinces: East Java, West Java, and Central Java. Clustering validity is confirmed through silhouette coefficient with the highest value of 0.795 for Cluster 2. These findings identify structural inequality between Java and outer Java regions, providing empirical foundation for the government to design more targeted educational equity policies, with priority on infrastructure rehabilitation and teaching staff augmentation in disadvantaged areas to achieve national educational justice. The research demonstrates that educational quality distribution in Indonesia remains heavily concentrated in Java, while remote and eastern regions face significant challenges in both physical infrastructure and human resources, requiring comprehensive government intervention strategies for sustainable educational development. Keywords: K-Means clustering, primary education, regional disparity, educational infrastructure, teaching personnel.