Analysis of Fuzzy C-Means Algorithm on Indonesian Translation of Hadits Text

Abstract

Hadith is the second source of Islamic religious law after the Al-Qur’an, in the hadith there are many chapters that discuss several cases and will be interesting to be combined with data mining techniques, especially text mining in order to group the hadith into several groups based on Matan (content hadith) automatically. Clustering is a technique of grouping data based on criteria, in clustering has several methods including K-Means and Fuzzy C-Means. This research will try to group the Indonesian translation of Hadith texts and compare K-Means and Fuzzy C-Means algorithms with some parameters and experiments that are determined. This comparison is used to determine the most accurate method in the Hadith clustering. The results of this research indicate that some of the parameters used to affect the results of cluster evaluation, especially in reducing data dimensions. In Silhouette Coefficient and F-Measure calculations, the Fuzzy C-Means method has an accuracy of 0.83079 and 0.97128 while the K-Means method has an accuracy of 0.67828 and 0.95078 with the results above show that the Fuzzy C-Means method is better in grouping the Indonesian hadith text.