International Journal Software Engineering and Computer Science (IJSECS)
Vol. 5 No. 1 (2025): APRIL 2025

K-Means Clustering Analysis of Poverty Data in Cilacap District

Setiawan, Kiki (Unknown)
Kastum (Unknown)
Pratama, Yuliya Putri (Unknown)



Article Info

Publish Date
01 Apr 2025

Abstract

Poverty stands as a complex structural obstacle within social development frameworks. The COVID-19 pandemic intensified poverty dynamics in Indonesia which saw poverty rates increase by 9.78% in March and reach 10.19% by September. Local Bureau of Statistics data shows that the poverty rate in Cilacap Regency dropped to 10.99% (around 191,000 people) in March 2024 from 10.68% (186,080 people) in March 2023. The study uses k-means clustering methodology for analysis and maps poverty-prone areas utilizing QGIS software. The analysis revealed 12 sub-districts and 14 neighborhood units (RW) alongside a single community unit (RT) that show unique poverty characteristics. The silhouette coefficient evaluation produced a 0.55 score which showed a moderate cluster structure and acceptable cluster placement. The research provides empirical evidence about poverty distribution which shows how data mining methods can enhance spatial socioeconomic studies. The study presents a detailed analysis of poverty stratification across Cilacap Regency through the application of sophisticated computational methods.

Copyrights © 2025






Journal Info

Abbrev

ijsecs

Publisher

Subject

Computer Science & IT

Description

IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer ...