Implementation of Fuzzy C-Means algorithm to classifying research topics in informatics department, UIN Sunan Gunung

Abstract

The more rapid and large number of electronic documents stored in University library repositories or Departments, such as scientific works from academicians including theses, research reports, etc., are available in the digital version. In the process of grouping the thesis title automatically it is hoped that it can help policy makers such as the head of the study program. In this case the researcher uses fuzzy c-means algorithm which can group data in clusters so that the data of a cluster has a high level of equality with each other. In the application there is a text mining method which is a development of data mining that can be applied to overcome thesis grouping problems or research data. The result is a web that can classify research data / thesis data with a total accuracy of 96%. This number is the accuracy given based on the performance of the fuzzy c-means algorithm on the system.

Implementation of Fuzzy C-Means for Clustering the Majelis Ulama Indonesia (MUI) Fatwa Documents

“…Therefore a method is needed to make the classification of these documents ease and simplify [2]. One of the methods that can be used is text mining [3], [4].…”