<![CDATA[The environment encompasses all living things and their surroundings, which interact to influence and sustain each other. In the era of globalization, advanced technologies have emerged that enhance human life, but these developments also have negative effects, such as environmental pollution. This research aims to categorize environmental pollution data in Indonesia, enabling further analysis of the clustering results. The study employs the K-Means algorithm to analyze data from 2024. This algorithm groups a set of objects into K clusters, with each object assigned to the nearest cluster based on average distance. The research findings indicate that the K-Means algorithm achieved a Silhouette Coefficient of 0.68 and identified two distinct clusters: Cluster 1 consists of 32 members characterized by lower numbers of environmental pollution while Cluster 2 includes 6 members that represent areas with greater environmental pollution. This study aims to provide the government with insights to address the rising issue of environmental pollution effectively.]]>
Copyrights © 2025
