Klasterisasi Kecamatan di Kabupaten Asahan Berdasarkan Indikator Pendidikan SMA Menggunakan K-Means
Keywords:
Clustering, Data Mining, Education Indicators, K-Means, Senior High SchoolAbstract
Disparities among districts in the number of schools, teachers, and students can signal unequal capacity in senior high school service provision. Building on this issue, the present study clusters the districts of Asahan Regency according to senior high school education indicators for the 2025/2026 academic year, applying the K-Means algorithm. Secondary data obtained from the Statistics of Asahan Regency, covering the number of schools, teachers, and students, were subsequently transformed into three ratios: student-to-teacher, student-to-school, and teacher-to-school. All variables were standardized through Z-scores, whereas the optimal number of clusters was determined using the Elbow Method together with the Silhouette Score and Davies-Bouldin Index. Out of 25 districts in total, only 18 could be included in the clustering process, while the remaining seven districts with zero values were examined separately. The evaluation results indicate that a two-cluster configuration performs best, yielding a Silhouette Score of 0.491 and a Davies-Bouldin Index of 0.701. The first cluster contains 16 districts characterized by a relatively low-to-moderate service scale, whereas the second cluster consists solely of West Kisaran City and East Kisaran City, both showing markedly higher concentrations of schools, teachers, and students. These findings are expected to serve as preliminary information for assessing the equitable distribution of senior high school services in Asahan Regency.
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