Cluster Modeling with K-Means on Provincial Data in Indonesia Based on Environmental Indicators

Amellia Harmaimun Hidayah; Diana Novitasari; Rosyidatul Kamila; Trimono; Muhammad Nasrudin

doi:10.59934/jaiea.v4i3.1143

Authors

Amellia Harmaimun Hidayah UPN "Veteran" Jawa Timur
Diana Novitasari UPN "Veteran" Jawa Timur
Rosyidatul Kamila UPN "Veteran" Jawa Timur
Trimono UPN "Veteran" Jawa Timur
Muhammad Nasrudin UPN "Veteran" Jawa Timur

DOI:

https://doi.org/10.59934/jaiea.v4i3.1143

Keywords:

Environmental Quality, K-Means, Clustering, Pollution, Population Density

Abstract

Population growth and economic activity in Indonesia significantly affect the quality of the environment. The government uses the Environmental Quality Index as a comprehensive measurement tool, which considers aspects of water, soil, and air pollution, as well as demographic variables such as population size and land area. This study aims to identify groups of 33 provinces in Indonesia based on pollution and demographic characteristics by applying the K-Means algorithm. The data, sourced from the Central Statistics Agency (BPS), underwent a series of stages: pre-processing, standardization, and evaluation using the Elbow, Silhouette Score, and Dunn Index methods. The clustering results identified two main groups. The first cluster consists of three provinces on the island of Java, which exhibit high population density and pollution levels. Meanwhile, the second cluster includes the remaining 30 provinces with more diverse characteristics. These findings are expected to support the formulation of more specific and evidence-based environmental policies.

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