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The rapid development of information technology has made the volume of information accessible by humans via internet unstoppable. This causes the reader to be able to sort out important information or summarize massive information. Readers need to summarize/summarize the amount of information into the main information that deserves to be studied. The process of summarizing/summarizing a lot of information from various sources is a difficult problem. Text summarization can be done automatically by a computer using artificial intelligence technology. This study proposes a clustering-based text summarization method with K-means clustering. The proposed method has been tested with a Rouge score using a benchmark dataset. Based on the test results, the proposed text summarization system is good, which has an F1 score of Rouge-1 = 49.37%, Rouge-2 = 38.18% and Rouge-L = 46.87%. The results obtained shows that this method is better than the three unsupervised methods that have been used previously, namely SumBasic, LSA and LexRank.

Peringkasan Ekstraktif Teks Bahasa Indonesia dengan Pendekatan Unsupervised Menggunakan Metode Clustering