Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

Nurhasanah Nurhasanah (Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala (USK), Indonesia)
Nany Salwa (Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala (USK), Indonesia)
Lyra Ornila (Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala (USK), Indonesia)
Amiruddin Hasan (Faculty of Teacher Training and Education, Universitas Syiah Kuala (USK), Indonesia)
Martahadi Mardhani (Faculty of Economics, Universitas Samudra (UNSAM), Indonesia)

Jurnal Sains Sosio Humaniora
Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Desember 2021

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.