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Winarni Suwarso
AMIK Al Muslim Tambun
Computer Science & IT

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Application of Fuzzy C-Means Clustering Method Using Matlab To Map the Potential of Rice Plant In Bekasi Regency Winarni Suwarso
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol 1, No 2 (2018): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : Institut Informatika dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/simada.v1i2.1134

Abstract

Based on the data of rice crops from BPS-Statistics of Bekasi Regency in the field of Food Crops, there are several sub-districts in Bekasi Regency with varying rice yields. Therefore, it is necessary to group the sub-districts with the highest potential of rice producers. Therefore, a method is needed to facilitate the classification of paddy producing districts. By Fuzzy C-Means clustering method, the division of rice-producing sub-districts can be done based on the area of rice harvest (Ha) and rice production (ton). In this research, clustering of potential sub-districts using the Fuzzy C-Means algorithm is aimed at facilitating the grouping of a sub-district with the largest and low rice yields. The result is an illustration that shows the subdistrict grouping based on the results of paddy farming.Keywords: Clustering; Data Mining; Fuzzy C-Means Algorithm
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