A COMPARATIVE STUDY OF K-MEANS AND SINGLE LINKAGE FOR REGIONAL CLUSTERING IN WEST KALIMANTAN IN 2024 BASED ON EDUCATIONAL INDICATORS

Ridho Alamsyah, Andina Putri Maharani, Dwi Vika Mutia, Sofiah Nur Alifah, Sofie Malika, Muhammad Riefky

Abstract


Education is a strategic investment in human resource development, as evidenced by several indicators, including the Average Years of Schooling (AYS), Expected Years of Schooling (EYS), Net Enrolment Rate (NER), and Gross Enrolment Ratio (GER). West Kalimantan Province faces the challenge of providing equal educational quality across regions. This issue has led to a low Human Development Index (HDI), ranking 30th of 34 provinces in Indonesia in 2024. These regional differences make it hard for the government to decide on the right policy actions. This study aims to group districts and cities in West Kalimantan based on their education quality indicators. It also compares the performance of two clustering methods, K-Means and Single Linkage, to find out which one produces the best results. The data used is secondary data from 2024, sourced from BPS West Kalimantan Province. The analysis included descriptive statistics, a data adequacy test, a multicollinearity test, and a cluster quality evaluation using the Elbow method based on Within-Cluster Sum of Squares (WCSS). At three clusters, K-Means produces a WCSS value of 26.6143, while Single Linkage produces a WCSS value of 33.7651. Therefore, K-Means with three clusters is selected as the optimal clustering method because it produces a lower WCSS value than Single Linkage. The K-Means clustering results consist of three groups with different characteristics based on the four education variables used in the study. These results can support local governments in formulating education policies tailored to the characteristics of each cluster.

Keywords:   Clustering,  Education,  K-Means

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References


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DOI: https://doi.org/10.20527/ragam.v5i2.19477

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RAGAM: Journal of Statistics and Its Application 

Program Studi Statistika, Fakultas MIPA, Universitas Lambung Mangkurat
Jalan A. Yani Km.36, Kampus ULM Banjarbaru, Kalimantan Selatan, Indonesia 70714

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RAGAM: Journal of Statistics and Its Application is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.