文章基本信息

标题：Analisis Perbandingan Pengelompokan Indeks Pembangunan Manusia Indonesia Tahun 2019 dengan Metode Partitioning dan Hierarchical Clustering
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作者：Arina Mana Sikana ; Arie Wahyu Wijayanto
期刊名称：Jurnal Ilmu Komputer
印刷版ISSN：1979-5661
出版年度：2021
卷号：14
期号：2
DOI：10.24843/JIK.2021.v14.i02.p02
语种：Indonesian
出版社：Jurnal Ilmu Komputer
摘要：Human Development Index (HDI) is an important indicator in measuring the level of success of the development of the quality of human life. Human Development Index clustering aims to divide the regions into groups based on Human Development Index for the region in 2019. Human Development Index clustering compares Partitioning Clustering and Hierarchical Clustering method to divide Human Development Index Indonesia in 2019. Partitioning Clustering method uses K-Means Clustering algorithm and Hierarchical Clustering method uses Agglomerative Ward Clustering algorithm. The results obtained are the best method for grouping provinces in Indonesia based on Human Development Index in 2019 is K-Means Clustering method with the optimum number of clusters is 6. This method gives Silhoutte Score o0,6291, Calinski-Harabasz Index 241,8875, dan Davies-Bouldin Index 0,3038. While the best method for grouping regencies in Indonesia based on Human Development Index in 2019 is K-Means Clustering method with the optimum number of clusters is 6. This method gives Silhoutte Score 0,5511, Calinski-Harabasz Index 1525,4007, dan Davies-Bouldin Index 0,5234.