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All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer)
Fadzly Maulana Hidayat
Universitas Buana Perjuangan Karawang
Computer Science & IT

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KLASTERISASI KABUPATEN DAN KOTA DI JAWA BARAT DALAM KASUS GIZI BURUK MENGGUNAKAN ALGORITMA K-MEANS DAN K-MEDOIDS Fadzly Maulana Hidayat; Tatang Rohana; Euis Nurlaelasari; Anis Fitri Nur Masruriyah
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1387

Abstract

Malnutrition is a disease whose incidence in Indonesia is increasing. Based on data from West Java Province, in 2019-2022 there were 1,986,890 toddlers who experienced nutritional problems. This high figure shows that the problem of malnutrition has not received adequate attention. This research will group districts and cities in West Java into three clusters. Cluster 1 (high), cluster 2 (medium), and cluster 3 (low) are based on the number of toddlers affected by malnutrition. It is hoped that this research can help the government in making decisions to overcome nutritional problems in West Java. The results of research on clustering cases of malnutrition in West Java using the K-Means algorithm include 3 clusters, Cluster 1 (high) which consists of 16 city districts. Cluster 2 (medium) consists of 10 city districts, Cluster 3 (low), while in the K-Medoids algorithm Cluster 1 (high) consists of 10 city districts. Cluster 2 (medium) consists of 4 city districts. Cluster 3 (low) consists of 13 districts and cities. The comparison results show that the K-Means algorithm is better using 3 clusters based on evaluation using the Silhouette Coefficient with a value of 0.617
Co-Authors Anis Fitri Nur Masruriyah Euis Nurlaelasari Tatang Rohana