Open AccessClassifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis
Author(s) -
Nurhasanah Nurhasanah,
Nany Salwa,
Lyra Ornila,
Amiruddin Hasan,
Martahadi Mardhani
Publication year - 2021
Publication title -
jurnal sains sosio humaniora
Language(s) - English
Resource type - Journals
eISSN - 2580-2305
pISSN - 2580-1244
DOI - 10.22437/jssh.v5i2.15801
Subject(s) - human development index , cluster (spacecraft) , cluster analysis , indonesian , index (typography) , geography , human development (humanity) , statistics , mathematics , economic growth , computer science , economics , linguistics , philosophy , world wide web , programming language
The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.