DOI: https://doi.org/10.14710/j.gauss.13.2.351-362

ANALISIS KLASTER KECAMATAN DI KOTA SURABAYA BERDASARKAN DATA PENDIDIKAN TAHUN 2022-2023

*Nanda Reza Handitia  -  Prodi S1 Matematika, Universitas Negeri Surabaya, Jl. Ketintang Wiyata No.36, Ketintang, Kec. Gayungan, Surabaya, Jawa Timur, Indonesia 60231, Indonesia
A'yunin Sofro scopus  -  Prodi S1 Sains Aktuaria, Universitas Negeri Surabaya, Jl. Ketintang Wiyata No.36, Ketintang, Kec. Gayungan, Surabaya, Jawa Timur, Indonesia 60231, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Education is an essential requirement for every individual to develop a country's human resources. The national education law emphasizes the importance of equal access, improving quality, and efficient education management to face global challenges. However, the equitable distribution of education in Indonesia, particularly through the zoning system, still faces significant challenges in major cities like Surabaya due to unequal distribution of educational access and facilities. This study compares the effectiveness of three non-hierarchical clustering analysis methods on Surabaya City's education data for 2022-2023. The data used was obtained from the latest publication of BPS Surabaya titled "Surabaya Municipality in Figures 2024". The data includes education data from 31 sub-districts in Surabaya, including the number of schools, students, and teachers at each level of education, namely elementary school, junior high school, and senior high school. The results of this research indicate that the K-Means method has the highest average coefficient value, with an average Silhouette Coefficient of 0.592. Therefore, the K-Means method has the most optimal cluster accuracy compared to other methods. These findings emphasize the need for more attention to sub-districts with low educational conditions to ensure equal access to education throughout the city of Surabaya.

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Keywords: Education; K-Means; K-Medoids; Fuzzy C-Means

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