Pengelompokan Kabupaten/Kota di Sumatera Utara Berdasarkan Indikator Kemiskinan dengan Menggunakan Analisis Klaster (Cluster Analysis)

Abstract

Background: North Sumatra has diverse characteristics of each region. Objective: This study aims to determine the grouping of districts/cities so that the North Sumatra provincial government can make policies and distribute social assistance proportionally to groups of districts/cities that match the criteria. Methods: Poverty clustering of districts/cities in North Sumatra Province uses the Euclidean Distance method with the Average Linkage clustering method. Using the Average Linkage method will be grouped into 2 clusters. Result: Cluster 1 is a cluster with a high poverty rate with 5 districts/cities. Cluster 2 is a cluster with a low poverty rate with 28 districts/cities. Conclusion: Poverty indicator characteristics are higher in districts/cities in cluster 1 compared to other districts/cities.