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All Journal Indonesian Journal of Statistics and Its Applications
Meilani, Detia
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Computer Science & IT Mathematics Other

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Grouping Provinces in Indonesia Based on the Causes of Stunting Variables using Hierarchical Clustering Analysis: Pengelompokan Provinsi di Indonesia Berdasarkan Peubah Penyebab Stunting Menggunakan Analisis Cluster Hierarki Meilani, Detia; Masjkur, Mohammad; Afendi, Farit M
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p32-43

Abstract

Stunting is a condition due to chronic malnutrition that causes children to be shorter in height compared to their age. The prevalence of stunting in Indonesia still exceeds the standards set by WHO. This study aims to classify provinces in Indonesia based on the characteristics of the causes of stunting. Cluster analysis is a statistical method used to group objects with similar characteristics. Province grouping is done using hierarchical cluster analysis consisting of Single Linkage, Complete Linkage, Average Linkage, Ward's method, and Centroid method. The Cophenetic correlation coefficient was used to determine the best cluster method and the optimal number of clusters using the Silhouette coefficient. The results show that the centroid method has the highest Cophenetic correlation coefficient with four clusters. The first cluster consists of 1 province with low stunting characteristics, the second cluster consists of 3 provinces with high stunting characteristics, the third cluster consists of 22 provinces with very high stunting characteristics, and the fourth cluster consists of 8 provinces with moderate stunting characteristics.
Co-Authors Afendi, Farit M Mohammad Masjkur