Using K-Means Clustering to Cluster Provinces in Indonesia

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Ansari Saleh Ahmar, Darmawan Napitupulu, Robbi Rahim, Rahmat Hidayat, Yance Sonatha, Meri Azmi

2018 Journal of Physics: Conference Series Vol. 1028 Issue 1 Conference paper Cited by 29 Quartile

Abstract

K-Means Clustering (KMC) is a technique used in performing data groupings. The data classification procedure is based on the degree of membership of each member. The purpose of this study is to group the existing Provinces in Indonesia based on Population Density, School Participation Rate, Human Development Index, and Open Unemployment Rate using K-Means Clustering. The result reveals 5 large clusters in each center in South Sumatra, Lampung, DKI Jakarta, Central Java, and West Kalimantan. © Published under licence by IOP Publishing Ltd.

Affiliations

Department of Statistics, Universitas Negeri Makassar, Makassar, 90222, Indonesia; AHMAR Institute, Makassar, 90222, Indonesia; Research Center for Quality System and Testing Technology, Indonesian Institute of Sciences, Jakarta, 12710, Indonesia; School of Computer and Communication Engineering, Universiti Malaysia Perlis, Perlis, Malaysia; Department of Information Technology, Politeknik Negeri Padang, Padang, 25166, Indonesia