Abstract:Donation data management is a complex challenge for amil zakat institutions in designing an effective marketing strategy for fundraising programs. In this study, the k-medoids algorithm was used to cluster the donation data with the aim of identifying patterns and characteristics of donors. The k-medoids algorithm was chosen because of its ability to handle unusual data and non-numeric attributes. Through clustering analysis, this study classifies donors based on attributes such as the number of donations, the… Show more
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