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Restin Welinda
Halu Oleo University
Computer Science & IT Control & Systems Engineering

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IMPLEMENTASI METODE FUZZY C-MEANS PADA SISTEM PENDUKUNG KEPUTUSAN PENENTUAN MUSTAHIK DI BAZNAS KENDARI Restin Welinda; Muh. Ihsan Sarita; Anita Puspita Dewi
semanTIK Vol 2, No 1 (2016): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (974.952 KB) | DOI: 10.55679/semantik.v2i1.737

Abstract

The process of determining the feasibility of recipients or  Mustahik  at Badan Amil Zakat Nasional Kota Kendari is still done manually. This is likely to cause a relatively high complexity and become ineffective both in time and the target of recipients. In this study,  Fuzzy C-Means  method was applied.  Fuzzy C-Means  is a data clustering technique in determining the truth of each data point within a cluster determined by the degree of membership. In this case the Fuzzy C-Means applied for a solution, each Mustahik candidate having the same data tendency will be included in a single cluster. Clustering is applied to  index criteria homes, businesses, and property to determine eligibility of Mustahik. The parameters included in this study is the number of cluster 2, rank / weighting 2, a maximum of 100 iterations, and the smallest error of 0.001. FCM calculation results  of the 200 test data obtained 144 data of Mustahik  candidate entitled to receive zakat. This suggests that the decision produced by the system using FCM method is equal to the manual determination through deliberation by the Badan Amil Zakat Nasional Kota Kendari. But time spent on this system by FCM method to determine recipients is more efficient and more effective than Kendari Zakat Amil Agency. Keywords— Cluster, Fuzzy C-Means, Mustahik, Decision Support Systems, Zakat.
Co-Authors Anita Puspita Dewi Muh. Ihsan Sarita