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Penerapan Clustering Kinerja Pengelolaan Sampah Daerah Indonesia dengan Algoritma K- Means Marisa; Belinda Eka Sarah Dewi; Satria, Satria; Panca Indah Lestari
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Waste management is a major problem in Indonesia that requires a comprehensive assessment. This study utilizes data from 2024 obtained from the National Waste Management Information System (SIPSN) managed by the Ministry of Environment and Forestry (KLHK), with performance indicators including the level of waste management and waste handling. The technique applied is K-Means Clustering with the use of the Elbow Method to determine the number of the most efficient clusters. The findings indicate that the most efficient clusters consist of three categories: cluster 0 (low-performance areas), cluster 1 (medium-performance areas), and cluster 2 (high-performance areas). Areas that show high performance are characterized by a high proportion of managed and handled waste that is almost 100%. Based on the analysis results, Bogor Regency is included in the group with the best performance in waste management, so it can be used as a reference for other regions in implementing successful and sustainable waste management strategies.