Implementation of Fuzzy C-Means for clustering the Majelis Ulama Indonesia (MUI) fatwa documents

Hariri, Fajar Rohman (2021) Implementation of Fuzzy C-Means for clustering the Majelis Ulama Indonesia (MUI) fatwa documents. Jurnal Online Informatika, 5 (1). pp. 1-10. ISSN 2527-1682

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Abstract

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 can make it easier and faster in the search for an Islamic law in Indonesia

Item Type:	Journal Article
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Fajar Rohman Hariri
Date Deposited:	10 Nov 2021 11:55

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