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All Journal Jurnal Ilmiah Sains dan Teknologi (SAINTEK)
Thiodas Heni Pakpahan
Universitas Logistik dan Bisnis Internasional
Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Physics

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Optimalisasi Distribusi Armada Sampah Melalui Segmentasi Wilayah Berbasis K-Means Clustering di Jawa Barat Thiodas Heni Pakpahan
Jurnal Ilmiah Sains dan Teknologi Vol. 10 No. 2 (2026): Jurnal Ilmiah Sains dan Teknologi
Publisher : Teknik Informatika Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/saintek.v10i2.4780

Abstract

Waste management in West Java faces an imbalance between waste volume and fleet capacity. This study optimizes fleet distribution through regional segmentation using K-Means Clustering by considering demographic, economic, and waste management factors based on 2023 Open Data Jabar. The analysis identifies three clusters with distinct characteristics and fleet needs. Cluster 0 consists of densely populated, small areas requiring an average of 3 arm rolls, 4 compactor trucks, and 7 dump trucks. Cluster 1 covers large, sparsely populated regions needing 7 arm rolls, 10 compactor trucks, and 18 dump trucks. Cluster 2 represents densely populated areas with high GRDP, demanding 12 arm rolls, 17 compactor trucks, and 32 dump trucks. Recommendations include route optimization for Cluster 0, zoning strategies for Cluster 1, and smart waste management implementation for Cluster 2 as policy references to enhance waste management efficiency
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