Spatial Analysis of Waste Management Facility Distribution Using GIS
DOI:
https://doi.org/10.26877/asset.v6i4.996Keywords:
Affordability, Buffering, Nearest Neighbor Analysis, Geospatial Analysis, Waste BanksAbstract
Recently, waste has become an extraordinary phenomenon that has attracted the attention of all levels of society: authorities, local governments, environmentalists, and regional stakeholders at the village level. Based on DIY Regional Regulation No. 3 of 2013 concerning the Management of Household Waste and Waste Similar to Household Waste and Sleman Regency Regional Regulation No. 6 of 2023 concerning the Implementation of Waste Management, efforts to minimize the amount of waste are made by each waste bank collaborating with TPS3R in Sleman Regency. Based on temporary data from 178 waste banks, there are 97 active waste banks and 32 TPS3R in Sleman Regency. The objectives of this study are (1) To determine the distribution pattern of active waste banks in Sleman Regency and (2) To determine the accessibility of active waste banks to TPS3R locations. This study uses the nearest neighbour analysis method, and the accessibility of active waste bank locations to TPS3R locations is measured using the buffering method—data processing using a Geographic Information System (GIS). The results of this study indicate (1) the distribution pattern of active waste banks in Sleman Regency based on the nearest neighbour ratio value is 0.861485 (<1), indicating a spatial pattern that tends to be clustered or spread in groups; (2) the accessibility of active waste banks to the TPS3R location has not shown an even pattern, from 32 TPS3R only 10 TPS3R have two waste banks, the rest 0 - 8 waste banks. The buffering distance shows that the closer the two locations are, the more effective and efficient waste management will be, with a maximum accessibility distance of 4.1 km.
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