PENGELOMPOKAN KABUPATEN/KOTA DI JAWA TENGAH MENGGUNAKAN METODE K-MEANS DAN FUZZY C-MEANS
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(*) Corresponding Author
Abstract
The Poverty is still a serious problem, especially in Indonesia. Central Java is
the province with the highest percentage of poor people in Java Island 13, 19%,
the figure is above the national poverty rate. In this research will be an analysis
of the factors affecting poverty in Central Java. The statistical approach used in
this case is cluster analysis. Cluster analysis is an analysis that aims to classify
an object (region) based on similarity characteristics of data. The method used
is the method of K-Means and Fuzzy C-Means. The object of research is
grouped into 4 clusters. The result of grouping shows that K-Means method is
the best method based on SW and SB ratio of 0.124.
Keywords: Data Mining, K-means, Fuzzy C-Means
the province with the highest percentage of poor people in Java Island 13, 19%,
the figure is above the national poverty rate. In this research will be an analysis
of the factors affecting poverty in Central Java. The statistical approach used in
this case is cluster analysis. Cluster analysis is an analysis that aims to classify
an object (region) based on similarity characteristics of data. The method used
is the method of K-Means and Fuzzy C-Means. The object of research is
grouped into 4 clusters. The result of grouping shows that K-Means method is
the best method based on SW and SB ratio of 0.124.
Keywords: Data Mining, K-means, Fuzzy C-Means
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