Jurnal Nasional Teknologi Informasi dan Aplikasinya
Vol 2 No 3 (2024): JNATIA Vol. 2, No. 3, Mei 2024

Algoritma K-Means untuk Clustering Provinsi di Indonesia Berdasarkan Kasus Stunting

Julianti, Syelvia (Unknown)
Widiartha, I Made (Unknown)



Article Info

Publish Date
01 May 2024

Abstract

Stunting is a nutritional issue that poses a global challenge, especially in developing countries like Indonesia. According to UNICEF, Indonesia ranks among the top five countries with the highest stunting prevalence. To address this issue, clustering provinces in Indonesia each year can help ensure equitable food distribution and other resources. This can be done using the K-Means clustering algorithm, with the optimal number of clusters determined by the elbow method and evaluated using the silhouette coefficient and Davies-Bouldin index. The optimal number of clusters was found to be 3, with a silhouette coefficient of 0.50 and a Davies-Bouldin index of 0.70. In 2020, there were 15 provinces in cluster 1, 6 provinces in cluster 2, and 17 provinces in cluster 3. In 2021, 15 provinces were in cluster 1, 17 in cluster 2, and 6 in cluster 3. In 2022, there were 17 provinces in cluster 1, 14 in cluster 2, and 7 in cluster 3. In 2023, 5 provinces were in cluster 1, 14 in cluster 2, and 19 in cluster 3. By 2024, there were 18 provinces in cluster 1, 17 in cluster 2, and 3 in cluster 3. Keywords: Stunting, K-Means, Elbow Method, Silhouette Coefficient, Devies Bouldin Index

Copyrights © 2024






Journal Info

Abbrev

jnatia

Publisher

Subject

Computer Science & IT

Description

JNATIA (Jurnal Nasional Teknologi Informasi dan Aplikasinya) merupakan jurnal yang berfokus pada teori, praktik dan metodologi seluruh aspek teknologi di bidang ilmu dan teknik komputer serta ide-ide produktif dan inovatif terkait teknologi baru dan sistem informasi. Jurnal ini memuat makalah ...