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All Journal ComTech: Computer, Mathematics and Engineering Applications
Mikhael Pramodana Agus
Bina Nusantara University
Computer Science & IT Engineering Mathematics

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Single Document Automatic Text Summarization using Term Frequency-Inverse Document Frequency (TF-IDF) Hans Christian; Mikhael Pramodana Agus; Derwin Suhartono
ComTech: Computer, Mathematics and Engineering Applications Vol. 7 No. 4 (2016): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v7i4.3746

Abstract

The increasing availability of online information has triggered an intensive research in the area of automatic text summarization within the Natural Language Processing (NLP). Text summarization reduces the text by removing the less useful information which helps the reader to find the required information quickly. There are many kinds of algorithms that can be used to summarize the text. One of them is TF-IDF (TermFrequency-Inverse Document Frequency). This research aimed to produce an automatic text summarizer implemented with TF-IDF algorithm and to compare it with other various online source of automatic text summarizer. To evaluate the summary produced from each summarizer, The F-Measure as the standard comparison value had been used. The result of this research produces 67% of accuracy with three data samples which are higher compared to the other online summarizers.
Co-Authors Derwin Suhartono Hans Christian