Peringkas dokumen berbahasa indonesia berbasis kata benda dengan BM25

Abstract

This research develops summarization of Indonesian documents based on nouns. The problem in this study is that high number of digital documents makes it difficult for the reader to find the desired information. We use cosine similarity, content overlap, and Okapi BM25 in the summarization. This research used newspaper articles from previous research. In the process of summarization, before calculating the similarities, the documents were preprocessed using stoplist, stemming, and selection of nouns. Then, the documents were ranked using PageRank. We used kappa measure to evaluate the level of agreement among evaluators in assessing the relevance of the summaries. Dice coefficient was used to compare automatic summarization to manual ones. Based on the observations, we find that Okapi BM25 is better than cosine similarity and content overlap.