Abstract:The rapid growth of the Indonesian language content on the Internet has drawn researchers' attention. By using natural language processing, they can extract high-value information from such content and documents. However, processing large and numerous documents is very timeconsuming and computationally expensive. Reducing these computational costs requires attribute reduction by removing some common words or stopwords. This research aims to extract stopwords automatically from a large corpus, about seven milli… Show more
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