<![CDATA[Poverty is a serious problem facing Indonesia, especially in developing regions such as Aceh, and can hinder national progress. Poverty involves various aspects, such as economic conditions, housing, and individual social capabilities. The variability of poverty data between regions is influenced by various factors, including social assistance, income, and other social factors. Therefore, solutions are needed to better manage and understand poverty data in Aceh. Two approaches that can be taken to overcome this challenge are the k-means clustering method and geographic information systems (GIS). The k-means clustering method is a statistical tool that allows researchers to group regions based on poverty levels, helping to identify relevant patterns. Meanwhile, GIS is used to analyse and visualise poverty data in the form of maps, facilitating understanding of poverty distribution patterns in Aceh. The development of a web-based geographic information system can also facilitate public and government access to poverty data in Aceh, increasing transparency and participation in addressing poverty issues. The results of this system will produce three groups of regions, namely non-poor, poor and very poor. Furthermore, this system has an accuracy of 93% similarity with the results conducted by BPS Lhokseumawe and Alu O Village.]]>
Copyrights © 2026
