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Apr 21, 2025
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May 7, 2025
Published
May 9, 2025
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Abstract

Abstract


Language has an important role in human life. With language, humans can communicate and exchange ideas with each other. However, the diversity of ethnic groups in Indonesia means that Indonesia has a variety of regional languages, therefore regional languages can make it difficult to convey information and communication. This research aims to identify the Kedang language and the Lamaholot language in text form. Identification is carried out to find out the language of each region using computerized technology. This identification uses a classification technique using a method, namely NAIVE BAYES WITH TF-IDF FEATURES. This method is used to identify the language according to the text that has been entered and then calculate the accuracy value. The identified data is 2000 sentences, so it can be seen which methods are effective and can be used to identify language. The research results found that this method was quite effective in identifying Kedang language with an accuracy value of 0.93 or 93%. And Lamaholot language with an accuracy value of 0.93 or 93%. And there are 63 examples of Kedang language and 58 examples of Lamaholot language


Keywords: Regional Languange Classification, TF-IDF, Naïve Baye

Keywords

Keywords: Regional Languange Classification, TF-IDF, Naïve Baye

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How to Cite
Ladopurab, B., Rahman, A. Y., & Pahlevi, R. (2025). Classification of Local Language Texts in Lembata Regency Using Naïve Bayes with TF-IDF Features. Edutran Computer Science and Information Technology, 3(1), 1-10. https://doi.org/10.59805/ecsit.v3i1.144

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