Categorizing document by fuzzy C-Means and K-nearest neighbors approach

Increasing of technology had made categorizing documents become important. It caused by increasing of number of documents itself. Managing some documents by categorizing is one of Information Retrieval application, because it involve text mining on its process. Whereas, categorization technique could be done both Fuzzy C-Means (FCM) and K-Nearest Neighbors (KNN) method. This experiment would consolidate both methods. The aim of the experiment is increasing performance of document categorize. First, FCM is in order to clustering training documents. Second, KNN is in order to categorize testing document until the output of categorization is shown. Result of the experiment is 14 testing documents retrieve relevantly to its category. Meanwhile 6 of 20 testing documents retrieve irrelevant to its category. Result of system evaluation shows that both precision and recall are 0,7.