Optimizing Zakat Distribution with GIS and Data Mining in Community Empowerment at BAZNAS Deli Serdang

Authors

  • Sinta Dara Efita Universitas Islam Negeri Sumatera Utara, Indonesia
  • Triase Triase Universitas Islam Negeri Sumatera Utara, Indonesia
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DOI:

https://doi.org/10.51519/journalisi.v6i4.942

Keywords:

zakat distribution, Geographic Information System, K-means clustering, social welfare, Deli Serdang

Abstract

This research aims to develop an information system that utilizes Geographic Information System technology to map and analyze the distribution of zakat effectively in Deli Serdang Regency. The methods used include collecting data on zakat recipients and applying the K-means grouping method to identify distribution patterns in 22 districts. The results of the study show that there are three groups of zakat recipients: High Recipients, Medium Recipients, and Low Recipients. Tanjung Morawa was identified as the district with the highest number of zakat recipients, namely 239 people, which shows a significant need. The K-Means algorithm plays an important role in identifying areas that need help, so this Geographic Information System-based grouping is proven to improve the efficiency of zakat resource allocation. This allows BAZNAS to target assistance more precisely and strategically. This study recommends the use of this approach to optimize zakat management and support community economic empowerment, as well as reduce social inequality in the region.

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Published

2024-12-31

Issue

Vol. 6 No. 4 (2024): December

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Articles

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How to Cite

[1]
S. D. Efita and T. Triase, “Optimizing Zakat Distribution with GIS and Data Mining in Community Empowerment at BAZNAS Deli Serdang”, journalisi, vol. 6, no. 4, pp. 3087–3103, Dec. 2024, doi: 10.51519/journalisi.v6i4.942.

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