Published: 2025-04-14
Perbandingan Metode K-Means dan Hierarchical Clustering dalam Pengelompokan Data Penduduk Miskin di Kabupaten Cianjur
DOI: 10.35870/ljit.v3i1.4028
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Abstract
Penelitian ini membahas perbandingan antara dua metode klasterisasi, yaitu K-Means dan Hierarchical Clustering, dalam mengelompokkan data penduduk miskin di Kabupaten Cianjur pada periode 2018-2021. K-Means digunakan untuk membagi data ke dalam jumlah klaster tertentu yang telah ditentukan sebelumnya, sementara Hierarchical Clustering memungkinkan pembentukan klaster berbasis hierarki tanpa memerlukan jumlah klaster awal. Hasil analisis menunjukkan bahwa K-Means memiliki keunggulan dalam hal kecepatan dan efisiensi, terutama untuk dataset besar dengan distribusi data yang seragam. Di sisi lain, Hierarchical Clustering lebih efektif dalam mengungkap pola yang kompleks dan menawarkan visualisasi dendrogram untuk analisis mendalam. Dengan menggunakan kedua metode ini, pengambilan keputusan terkait kebijakan sosial dapat lebih terarah, berdasarkan analisis data yang akurat dan mendalam. Penelitian ini memberikan kontribusi penting untuk mendukung program pengentasan kemiskinan secara lebih optimal.
Keywords
Clustering ; Hierarchical Clustering ; K-Means ; Kemiskinan ; Pengambilan Kebijakan
Article Information
This article has been peer-reviewed and published in the LANCAH: Jurnal Inovasi dan Tren. The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 3 No. 1 (2025)
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Section: Articles
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Published: %750 %e, %2025
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License: CC BY 4.0
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Copyright: © 2025 Authors
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DOI: 10.35870/ljit.v3i1.4028
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Ihsan Pratama Putra
Teknik Informatika, STMIK-IM, Indonesia
Avram Fadhillah
Teknik Informatika, STMIK-IM, Indonesia
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