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Cluster Mapping of Waste Exposure Using DBSCAN Approach: Study of Spatial Patterns and Potential Distribution in Bantul Regency
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Researchers used spatial clustering analysis to map waste accumulation hotspots in the Bantul Regency of Indonesia, where landfill capacity has been repeatedly exceeded. The study identified clustered patterns of waste buildup near markets and collection points, information that could help local governments target interventions to reduce long-term microplastic contamination risks from mismanaged waste.
High level of plastic waste production is a common issue in various places, including the Special Region of Yogyakarta province. It is proven that the Piyungan Integrated Waste Disposal Site (TPST) or Final Disposal Site (TPA) in Bantul Regency has been closed several times due to capacity exceeding the quota and some blockages from residents around the TPA. Issues related to microplastic contamination resulting from discarded plastic waste are fascinating to study, considering the long-term impact of microplastic contamination on human health. This research aims to map the distribution of locations with the potential for waste accumulation to reduce the negative consequences of microplastic contamination. The population used included TPS and markets in Bantul District, with the sample being the distribution of TPS and market points in Bantul District in 2023. The results of checking the point distribution pattern using the quadrant and nearest neighbor method showed that the distribution of waste accumulation points had a clustered design; thus, it could be continued with cluster analysis using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method. Meanwhile, the number of clusters was determined iteratively from a combination of DBSCAN parameters (MinPts and Epsilon). The best method was evaluated based on the Silhouette Coefficient (SC) value, which in this case was 0.78 (MinPts 7 and Eps 1500) and included in the strong category. Subsequently, exploration was carried out by reducing the MinPts value and the lowest limit value of strong SC.
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