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Mursawal, Mursawal
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Computer Science & IT

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Journal : Jurnal Informatika dan Rekayasa Perangkat Lunak

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Klasterisasi Wilayah Kabupaten/Kota di Sulawesi Tenggara berdasarkan Produksi Bahan Pangan menggunakan Algoritma K-Means Clustering Mursawal, Mursawal; Saputra, Rizal Adi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Abstract

Food ingredients are ingredients produced from agricultural products that are used to make food. These foods consist of vegetables, meat, nuts, sweet potatoes, and so on. Southeast Sulawesi Province is one of the provinces that has a fairly high amount of food production in Indonesia. The application of the K-Means clustering algorithm is used to group districts/cities in Southeast Sulawesi based on food production results. The method used in this study is CRISP-DM with the K-Means clustering algorithm. There are 17 districts/cities in Southeast Sulawesi used in this study. There are 7 types of food ingredients that will be used in the study, namely rice, corn, cassava, sweet potatoes, peanuts, soybeans, and green beans. The results of this study are 1 district/city that has a high level of food production, 4 districts/cities have a moderate level of food production, and 12 districts/cities have a low level of food production. The test results using the Davies Bouldin index are cluster 2 which has the best cluster quality because the results obtained from cluster 2 are 0.30, where the smaller the results obtained, the better the cluster.
Co-Authors Rizal Adi Saputra