Analisis Fitur Kalimat untuk Peringkas Teks Otomatis pada Bahasa Indonesia

Abstract

Abstract— Automatic Text Summarization (ATS) is a technique to create a summary of the document automatically by using computer applications to produce the most important information from the original document. Features are required to perform weighting of sentences, including Log-TFISF (term frequency index sentence frequency), sentence location, sentence overlap, title overlap and sentence relative length. This research conducted an analysis of five features in order to determine the weights of each feature that will get the results of a coherent summary. The five features are implemented in automated text summarization system in Indonesian language that was developed using the method of relative importance of topics. Results from experiments show that sentence location feature has the highest F-Measures namely 0.46 and then consecutive sentence overlap, title overlap, sentence relative length and Log-TFISF, with a value of 0.42, 0.42, 0.35 and 0.32. Relative weights of feature extraction consecutive from the largest are sentence location, sentence overlap, title overlap, sentence relative length and Log-TFISF with a value of 0.25, 0.22, 0.22, 0.19 and 0.12. These relative weights are implemented on ATS, so we get accuracy of 70.62%. It is more accurate 2,86% than without relative weights which accuracy of 67,72%..

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Keywords— Automatic Text Summarization (ATS), Log-TFISF, sentence location, sentence overlap, title overlap, sentence relative length, bahasa Indonesia