Open AccessDATA MINING DALAM PENGELOMPOKAN JENIS DAN JUMLAH PEMBAGIAN ZAKAT DENGAN MENGGUNAKAN METODE CLUSTERING K-MEANS (STUDI KASUS: BADAN AMIL ZAKAT KOTA BENGKULU)
Author(s) -
Prahasti Prahasti
Publication year - 2018
Publication title -
jurti (jurnal teknologi informasi)/jurti (jurnal teknologi informasi)
Language(s) - English
Resource type - Journals
eISSN - 2615-2738
pISSN - 2580-7927
DOI - 10.36294/jurti.v1i2.298
Subject(s) - cluster analysis , centroid , data mining , cluster (spacecraft) , computer science , distribution (mathematics) , mathematics , combinatorics , artificial intelligence , mathematical analysis , programming language
Abstrack - This research applies data mining by grouping the types and recipients of zakat. The application is done by the k-means clustering algorithm where the data to be entered is grouped by education and type of work in the distribution of zakat. Then a cluster is formed using the centroid value to determine the closest center point of distance between data. In the k-means clustering algorithm data processing is stopped in the iteration count of the data has not changed (fixed data) from the data that has been grouped. The test is done by using the RapidMiner software experiment conducted by the k-means clustering method which consists of input units, data processing units and output units, k-means clustering grouping data 1-2-1-1, 1-2-1-2 and 3-4-3-4. The results obtained from these tests are grouping the distribution of zakat with each cluster not the same. The test results are displayed in slatter graph. Keywords - Data Mining, K-Means Clusttering, Zakat