Metode K-Means SAW dalam Seleksi Penerima Dana akat pada Badan Amil akat - Yunita; Rusdi Efendi; Dian Palupi Rini (Sekolah Tinggi Manajemen Informatika dan Komputer PalComTech, 2019)
akat is an obligation for Muslims as the implementation of the Five Pillars of Islam including sadaah and infa. The higher the communitys awareness to pay zakat, the more amil zakat boards establish in the community, one of them is Pertaminass amil zakat body (BAMA) in Palembang. The problem currently encountered is that the determination of the recipient of zakat funds must compare the results of the survey one by one so that it is obtained who is most entitled to receive the zakat funds. This procedure may cause relatively high complexity both of time, the accuracy of the results and may affect the target recipient of zakat. The purpose of this study is to minimize the mistakes of BAMA officers in the distribution of zakat funds, so that a decision support system is needed in determining the recipient of zakat funds where the system has been determined based on criteria. K-Means Clustering is a method that groups data according to each cluster. Simple Additive Weighting (SAW) is a method used for the ranking process by using preference values. In this study, the K-Means Clustering method will divide the zakat recipient data according to the distance calculated from the initial position between the zakat recipient data, then the SAW method will sort the zakat recipient data based on each cluster.