Open AccessImplementation of Fuzzy C-Means for Clustering the Majelis Ulama Indonesia (MUI) Fatwa Documents
Author(s) -
Fajar Rohman Hariri
Publication year - 2021
Publication title -
join (jurnal online informatika)
Language(s) - English
Resource type - Journals
eISSN - 2528-1682
pISSN - 2527-9165
DOI - 10.15575/join.v6i1.591
Subject(s) - cluster analysis , indonesian , similarity (geometry) , fuzzy logic , computer science , value (mathematics) , data mining , fuzzy clustering , silhouette , institution , k means clustering , information retrieval , artificial intelligence , political science , law , machine learning , linguistics , image (mathematics) , philosophy
Since the Indonesian Ulema Council (MUI) was established in 1975 until now, this institution has produced 201 edicts covering various fields. Text mining is one of the techniques used to collect data hidden from data that form text. One method of extracting text is Clustering. The present study implements the Fuzzy C-Means Clustering method in MUI fatwa documents to classify existing fatwas based on the similarity of the issues discussed. Silhouette Coefficient is used to analyze the resulting clusters, with the best value of 0.0982 with 10 clusters grouping. Classify fatwas based on the similarity of the issues discussed can make it easier and faster in the search for an Islamic law in Indonesia.