Implementasi Clustering K-Medoids dalam Pengelompokan Kabupaten di Provinsi Aceh Berdasarkan Faktor yang Mempengaruhi Kemiskinan

Freditasari Purwa Hidayat (Islamic University of Indonesia)
Royhan Pina Putra (Islamic University of Indonesia)
M Dendi Alfitrah (Islamic University of Indonesia)
Edy Widodo (Islamic University of Indonesia)

Indonesian Journal of Applied Statistics
Vol 5, No 2 (2022)

The economy is one of the parameters to see how the development of a country. Ending poverty anywhere and in any form is goal 01 of the Sustainable Development Goals (SDGs) program. Until now, poverty has become one of the main problems in Indonesia, so poverty must be a concern of the government. Based on data from the Central Statistics Agency (BPS) shows that as of September 2020 the percentage of poor people in Aceh Province is still the highest on the island of Sumatra, which is 15.43%. The purpose of this study is to classify districts based on factors that affect poverty in Aceh Province. The method used in this study is the K-Medoids Cluster Analysis algorithm. The optimal number of clusters is 2 clusters with cluster 1 consisting of 11 districts and cluster 2 consisting of 12 districts. Cluster 1 has a higher percentage of poor population and poverty depth index than cluster 2, while cluster 2 has higher Gini Ratio, AHH, and RLS values than cluster 1.Keywords : Clusters, Economy, Poverty, SDGs