Perbandingan Metode K-Means dan Hierarchical Clustering dalam Pengelompokan Data Penduduk Miskin di Kabupaten Cianjur
DOI:
https://doi.org/10.35870/ljit.v3i1.4028Keywords:
Clustering, Hierarchical Clustering, K-Means, Kemiskinan, Pengambilan KebijakanAbstract
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.
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