INTEGRATED TEXT CLASSIFICATION METHOD FOR INDONESIAN NEWS DOCUMENTS

Textclassification hasbeena popular research field in the areaof computer science. It
deals with the assignment of labels into a group of similar textual document.
However, there have been very limited approaches which are focused on improving
the unique character of news corpus, even less for Indonesian news document. Apart
from that, onlyfew were aimed at categorizing and identifying topics. The aim of this
study is to develop a text classifier for Indonesian news articles based on Bracewell's
algorithm and top-n keywords selection method to improve the online news corpora
challenges: the significant difference among articles m one category, the high
computational time,andthe possibility of a new, previously-never-existed topic.