Clustering Regencies/Cities Vulnerable to Air Pollution in the Java Island: Fuzzy Geographically Weighted Clustering
DOI:
https://doi.org/10.34123/jurnalasks.v17i2.618Keywords:
Air Pollution, Artificial Bee Colony (ABC), Environment, Fuzzy C Means (FCM), Fuzzy Geographically Weighted Clustering (FGWC)Abstract
Introduction/Main Objectives: Air pollution has become a critical global concern with substantial effects on human health and the environment. Background Problems: Java Island in Indonesia, recognized for its high population density and industrial activities, necessitates focused effort in resolving this issue. Novelty: While air pollution research has been enormous, there has been no effort to cluster regencies or cities on Java Island utilizing spatially-based data. This research seeks to cluster regencies and cities on Java Island according to air pollution levels and to compare geodemographic and non-geodemographic clustering methodologies. Research Methods: This study employs secondary data regarding air pollution, obtained from the Openweather API. This study employs a geodemographic clustering technique, namely fuzzy geographically weighted clustering (FGWC), optimized by the artificial bee colony (ABC) algorithm. Finding/Results: The study findings indicate that the geodemographic clustering method ABCFGWC surpasses Fuzzy C-Means (FCM) according to the TSS (Tang-Sun-Sun) index. The data reveal that the Greater Jakarta or Jabodetabek area and its adjacent territories are more susceptible to air pollution. The findings of this study are expected to enhance the spatial planning and mapping of air pollution management strategies on Java Island.
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