Pengelompokan pembagian zakat dengan menggunakan metode clustering k-means

Abstract

Zakat is a worship that involves property. Zakat is also included in the fourth pillar of Islam which has the aim of purifying the assets of every Muslim by setting aside a portion of his wealth, if it has reached the time and the amount is given to those who are entitled to receive it. The collection and distribution of zakat is usually handled by the Amil Zakat Agency (BAZ) in every region of Indonesia, one of which is in Pekanbaru. In accordance with the regulations, there are two stages in providing assistance to mustahik, namely conducting interviews and field observations, then determining the nominal amount of assistance given to the Mustahik category of recipients of zakat 1, zakat 2, and zakat 3. Problems that are often encountered in determining potential recipients assistance is a way of selecting Mustahik which still uses the manual method, so that it often causes problems such as the length of the selection process and the occurrence of miscalculations so that the results of Mustahik's selection become inaccurate. For that, it is necessary to create analysis that can process data into information. Data mining is a process for processing data into information using statistical techniques, AI, and machine learning. There are many methods in data mining. In this study using the k-means clustering and for testinguse Davies Bouldin Index. based on testing using the davies bouldin index (DBI) cluster 4 is the best cluster with a value of 0.671, where the lower the value, the better the cluster.