Rezki, Ilvinda
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The Use of K-Means Clustering Algorithm to Determine Potential Region for Zakat Distribution Based on Social and Economic Data in Indonesia 2023 Dibah, Farah; Rezki, Ilvinda
International Journal of Zakat Vol 10 No 3 (2025): International Journal of Zakat
Publisher : Center of Strategic Studies (PUSKAS) BAZNAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37706/ijaz.v10i3.674

Abstract

Poverty remains a significant challenge in many developing nations, including Indonesia. Poverty is also considered a problem caused by uneven economic growth. An effective approach to reducing poverty is through the equitable distribution of zakat, which can help narrow the disparity between the wealthy and those in need. Equitable distribution of zakat can be done by determining the level and potential of poverty in each province in Indonesia. To find out the poverty potential in each province in Indonesia, it is necessary to conduct a cluster analysis by looking at several poverty and economic growth variables. Cluster analysis is an analytical method employed to classify similar objects or individuals based on multiple criteria. Cluster analysis specifically used is k-means clustering which divides provinces in Indonesia into groups by identifying any similarities in the economic growth variables of each province. This analysis aims to categorize provinces in Indonesia based on economic conditions and levels, thereby assisting the government and zakat institutions in the effective distribution of zakat.