Likelihood calculation classification for Indonesian language news documents

Text categorization has been an important research area that seeks to classify textual documents into a group of predetermined categories. Unfortunately, the interest towards Indonesian news classification has been very little. In this paper, we propose a text categorization algorithm based on Bracewell method that uses the likelihood calculation between the article and the category´s keywords. Through experiments, the algorithm succeeded in classifying Indonesian news corpus with accuracy as high as 93,84% in offline environment, 93,82% in online environment, and 80% benchmarking against human evaluation.