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Galih Wiratmoko
Universitas Muhamadiyah Surakarta, Indonesia
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics

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Journal : jurnal syntax admiration

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Evaluating the Effectiveness of the LexRank and LSA Algorithm in Automatic Text Summarization for Indonesian Language Galih Wiratmoko
Jurnal Syntax Admiration Vol. 5 No. 9 (2024): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v5i9.1483

Abstract

The aim of this study is to evaluate how effective the Lexrank algorithm and Latent semantic analysis (LSA) are in automatic text summarization for the Indonesian language. This research focuses on natural language processing and handling of excessive data. We applied both algorithms to generate text summaries using the INDOSUM dataset, which contains about 20,000 news articles in Indonesian with manual summaries. To assess performance, the ROUGE metric was used, which includes aspects of precision, recall, and F1 score. In all tested metrics, LSA outperformed Lexrank. LSA had a precision of 0.57, recall of 0.67, and an F1 score of 0.59, whereas Lexrank had a precision of 0.46, recall of 0.52, and an F1 score of 0.48. These result indicate that LSA is better at gathering important information from the original text than Lexrank.
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