Clustering of the Best Senior High Schools in Serdang Bedagai Regency Using the K-Means Method

Tania Annisa Siagian; Nurdin Nurdin; Munirul Ula

doi:10.30865/json.v6i4.8669

Authors

Tania Annisa Siagian Universitas Malikussaleh
Nurdin Nurdin Universitas Malikussaleh
Munirul Ula Universitas Malikussaleh

DOI:

https://doi.org/10.30865/json.v6i4.8669

Keywords:

K-Means, Clustering, Senior High School, Davies-Bouldin Index, Serdang Bedagai

Abstract

This study aims to cluster the best Senior High Schools (SMA) in Serdang Bedagai Regency using the K-Means method. Five evaluation indicators were used in the clustering process: accreditation, school status, number of teachers, achievements, and facilities. A total of 41 schools were analyzed using a non-hierarchical approach, with the optimal number of clusters determined through the Elbow Method, resulting in three groups: excellent, good, and fair. Data normalization was performed using the Min-Max method to ensure equal scaling among variables. The clustering results using the K-Means algorithm formed three clusters that represent the quality of schools based on transformed numerical data. The K-Means method proved capable of providing a general overview of school quality grouping, which can serve as a basis for policy-making to improve the quality of education in the region.

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