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Pendekatan Metode Partisi, Hierarki, dan Densitas dalam Pengelompokan Provinsi di Indonesia Berdasarkan Indeks Ekonomi Hijau Tahun 2023 Gufron, Fat’hul Mubin; Chisan, Innas Khoirun; Utami, Almira; Prakoso, Nur Yudha Jati; Kartiasih, Fitri
Jambura Journal of Probability and Statistics Vol 6, No 2 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i2.27734

Abstract

Sustainable economic development that maintains environmental balance is a top priority in Indonesia’s national development planning. One of the key indicators to measure this sustainability is the Green Economy Index (GEI). The Ministry of National Development Planning (Bappenas) assesses green economic development using 15 indicators across three pillars: economic, social, and environmental. This study aims to cluster Indonesian provinces based on the GEI. The clustering methods used include partition-based approaches (K-Means, K-Medoids), hierarchical (\textit{agglomerative clustering}), and density-based (OPTICS), with evaluation based on internal validity and stability. The results show that the hierarchical \textit{average linkage} method provides the most optimal clustering performance, dividing provinces into three main groups. Each cluster reflects different GEI characteristics, highlighting disparities in green development achievements across regions. Cluster 1 consists of one province with high economic scores but very low environmental scores; Cluster 2 includes five provinces strong in environmental performance but weak economically; and Cluster 3 contains 32 provinces with diverse characteristics in green economic practices. These findings are expected to support more targeted and region-specific policy formulation to promote equitable green economic development.