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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Automatic Extraction of Indonesian Stopwords

Author 1: Harry Tursulistyono Yani Achsan
Author 2: Heru Suhartanto
Author 3: Wahyu Catur Wibowo
Author 4: Deshinta A. Dewi
Author 5: Khairul Ismed

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2023.0140221

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 2, 2023.

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Abstract: The rapid growth of the Indonesian language content on the Internet has drawn researchers’ attention. By using natural language processing, they can extract high-value information from such content and documents. However, processing large and numerous documents is very time-consuming and computationally expensive. Reducing these computational costs requires attribute reduction by removing some common words or stopwords. This research aims to extract stopwords automatically from a large corpus, about seven million words, in the Indonesian language downloaded from the web. The problem is that Indonesian is a low-resource language, making it challenging to develop an automatic stopword extractor. The method used is Term Frequency – Inverse Document Frequency (TF-IDF) and presents a methodology for ranking stopwords using TFs and IDFs, which is applicable to even a small corpus (as low as one document). It is an automatic method that can be applied to many different languages with no prior linguistic knowledge required. There are two novelties or contributions in this method: it can show all words found in all documents, and it has an automatic cut-off technique for selecting the top rank of stopwords candidates in the Indonesian language, overcoming one of the most challenging aspects of stopwords extraction.

Keywords: Stopwords extraction; attributes reduction; TF-IDF; large corpus; Indonesian stopwords; NLP

Harry Tursulistyono Yani Achsan, Heru Suhartanto, Wahyu Catur Wibowo, Deshinta A. Dewi and Khairul Ismed, “Automatic Extraction of Indonesian Stopwords” International Journal of Advanced Computer Science and Applications(IJACSA), 14(2), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140221

@article{Achsan2023,
title = {Automatic Extraction of Indonesian Stopwords},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140221},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140221},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Harry Tursulistyono Yani Achsan and Heru Suhartanto and Wahyu Catur Wibowo and Deshinta A. Dewi and Khairul Ismed}
}


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