<![CDATA[Zakat is an asset collected from muzaki and then distributed to those who are entitled to receive, namely 8 asnaf consisting of very poor people, people who are lacking, zakat management officers, people who have just converted to Islam, people who have a lot of debt, slaves who want to be free, travelers, and those who fight in the way of Allah. In Al-Huda Mosque, the data of zakat recipients currently only displays names, addresses, the number of family dependents, and the amount of zakat distributed. Takmir does not yet know the recipients who are entitled to zakat in large or small amounts. Therefore, an algorithm is required to streamline the grouping of data on zakat recipients in Al-Huda Mosque based on data ratios such as the number of family dependents, work, home conditions, and transportation. This study applies the K-Means Clustering method approach to group zakat recipient data. Web-based applications are developed using PHP to make it easier to manage data and grouping effectively. As a result, 7 recipients received high priority recipients, 30 medium priority recipients, and 16 low priority recipients. Testing of data clusters with the Silhouette Coefficient method showed that 4 clusters have strong structural values. For future research, additional variables can be extracted and analyzed to maximize more accurate and comprehensive grouping results]]>
Copyrights © 2024
