Kaylista N.N.K
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Implementasi Algoritma K-Means Clustering Menggunakan Aplikasi Orange Untuk Mengetahui Pola Indeks Pembangunan Manusia Tahun 2022 Kaylista N.N.K; Nabiilah Khoirunnisaa; Gading Viewianti E.N.F; Ajif Yunizar Pratama Yusuf
Journal of Informatic and Information Security Vol. 4 No. 1 (2023): Juni 2023
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/m50n5t48

Abstract

The Human Development Index (HDI) is used as a statistical parameter to evaluate the progress and quality of human life in a country. Human development plans are measured through three basic aspects: a long and healthy life, knowledge, and a decent standard of living. The research focuses on the application of k-means algorithms to identify patterns and group 34 provinces in Indonesia based on indicators that form the 2022 HDI. These indicators include life expectancy (UHH), school life expectancy (HLS), average school time (RLS), and spending. This HDI grouping aims to identify the HDI variables that should be a priority in development. The results of the analysis showed the formation of two groups (clusters) through K-Means Cluster Analysis. Cluster 1 has provincial characteristics with high to very high values on UHH, HLS, RLS, and customized output. Meanwhile, Cluster 2 consists of provinces with medium to high values on UHH, HLS, RLS, and adjusted output.