Vol 2 No 1 (March 2026)
Articles

Spatial Analysis of Residential Areas in Densely Populated Regions of Bireuen City Using K-Medoids Clustering

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  • Ulfi,
  • Muhammad Rizka,
  • Hendrawaty
Ulfi
Politeknik Negeri lhokseumawe
Muhammad Rizka
Politeknik Negeri Lhokseumawe

Published 24-03-2026

Keywords

  • Clustering,
  • Density,
  • Area,
  • Silhoutte Score,
  • urban

Copyright (c) 2026 Ulfi, Muhammad Rizka, Hendrawaty

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Abstract

The rapid population growth in Bireuen City, Aceh, poses significant challenges for urban planning, particularly in managing high population density and various social issues. Based on data from the Central Bureau of Statistics, Aceh’s population increased by 2%, reaching 5.37 million people in 2019, with a population density ratio of 95 people per km². Bireuen City, with a population of 471,635, is experiencing rapid growth across diverse occupational backgrounds. This study aims to develop a web-based population density mapping system using the K-Medoids method to overcome the limitations of the K-Means method in handling outliers. The data used include district names, area size, number of ID cards, number of households, and total population. The K-Medoids algorithm groups the data into the nearest clusters, and the process is repeated until the clustering results become stable. The clustering results indicate three main clusters: Cluster 0 (medium density, Silhouette Score 0.70), Cluster 1 (low density, Silhouette Score 0.20), and Cluster 2 (high density, Silhouette Score 1). These findings are expected to assist the Central Bureau of Statistics in planning residential areas and managing urban development more effectively and efficiently.

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