UNLOCKING INSIGHTS: CLUSTER ANALYSIS OF THE ASNAF COMMUNITY IN PERLIS USING A HYBRID CLUSTERING MODEL

Authors

  • Rabiah Abdul Kadir Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Malaysia
  • Ummul Hanan Mohamad Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Malaysia
  • Mohamad Syahmi Shahril Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Malaysia

DOI:

https://doi.org/10.35631/IJLGC.1041006

Keywords:

Artificial Intelligence, Data Analytics, Clustering, Asnaf

Abstract

The main goal of the country is to eradicate poverty and make the lives of Muslims more prosperous. The Perlis Islamic Religious Council and Malay Customs Council (MAIPs) have always been committed to channeling assistance to the asnaf group since 2013 through the Kayuhan MAIPs Peduli program. The distribution of assistance to eligible groups has been carried out through 704 programs led by Tuanku Syed Faizuddin Putra Jamalullail. In determining the groups eligible to receive zakat, the zakat department will use the method of calculating and measuring the had kifayah. However, in determining the target among the selected asnaf, the support of digital technology that is growing rapidly today is still needed. With the support of digital technology that is capable of carrying out cluster analysis, the management of selecting and grouping these asnaf groups will be easy and effective for MAIPs in making decisions on assistance to target groups among the asnaf. This project conducts research and development of analytics dashboards that focus on grouping asnaf groups eligible to receive zakat, such as Fakir, Miskin, Amil, Muallaf, Al-Riqab, Al-Gharimin, Fisabilillah, and Ibnu Sabil. The analytics dashboards will be developed with artificial intelligence (AI) digital technology using a classification algorithm, namely Support Vector Machine (SVM), which is based on machine learning. This project involves five (5) phases of research and development, namely: (i) identifying features of asnaf groups for analysis purposes; (ii) designing a prototype based on machine learning; (iii) developing applications using the Support Vector Machine (SVM) algorithm; (iv) testing applications on a dataset of asnaf groups in Perlis; and (v) deploying applications to MAIPs to target assistance categories to selected asnaf groups. The results of this project are expected to increase the impact and services of the Kayuhan MAIPs Peduli program, which is one of the strengths of MAIPs in helping target groups among asnaf in Perlis. The developed analytics dashboard application also expands the reach and accessibility of services to other stakeholders in fostering innovation and collaboration in the same sector in Malaysia.

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Published

13-08-2025

How to Cite

Abdul Kadir, R., Mohamad, U. H., & Shahril, M. S. (2025). UNLOCKING INSIGHTS: CLUSTER ANALYSIS OF THE ASNAF COMMUNITY IN PERLIS USING A HYBRID CLUSTERING MODEL. INTERNATIONAL JOURNAL OF LAW, GOVERNMENT AND COMMUNICATION (IJLGC), 10(41). https://doi.org/10.35631/IJLGC.1041006