PENGELOMPOKAN PENYANDANG MASALAH KESEJAHTERAAN SOSIAL DI JAWA BARAT MENGGUNAKAN K-MEANS DAN FUZZY C-MEANS
DOI:
https://doi.org/10.34151/technoscientia.v15i1.3847Keywords:
Clustering, Davies Bouldin Index, Fuzzy C-means, K-meansAbstract
Social welfare problems still occur in some provinces in Indonesia, including in West Java. Social welfare problems cannot be completely overcome, but according to policy perceptions, they can be reduced, therefore analyses are required. Grouping data on people with social welfare problems to find out the best group based on the data will provide alternative policies and appropriate methods. The purpose of this study was to find the best group of people with social welfare problems using the k-means and fuzzy c-means methods based on the results of the DBI evaluation. The methods used for this grouping were the k-means and fuzzy c-means algorithm methods. From the results of this study, it was obtained the best 2 groups from the experiment of fuzzy c-means algorithms based on the smallest DBI assessment or close to 0 between the k-means and fuzzy c-means algorithms from each DBI value, they were k-means algorithm with value of 0.029 and fuzzy c-means algorithm with value of 0.006.
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