Classification Of Indonesian Slang Using Naïve Bayes And Decision Tree Methods On Social Media

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Published: Jul 19, 2022
DOI: https://doi.org/10.35335/mantik.v6i2.2647
Keywords:
Classification, Naïve Bayes, Decision Tre, Social Media
Issue
Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Section
Computer Science
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Article View : 148 Times

Main Article Content

Abdi Dharma
Universitas Prima Indonesia
Aditya Calderon Naibaho
Universitas Prima Indonesia
Lolo Mulatua Bancin
Universitas Prima Indonesia
Alhoi Andrew Jefferson
Universitas Prima Indonesia

Abstract

At this time the application of language that appears on social media is the application of slang as a character of current language development. This phenomenon deserves to be discussed because it can find out how much slang is used on social media. The source of the dataset for this research is the verbal form found on the author's personal social media such as Instagram and Tiktok obtained by the web scraping method as many as 2,000 samples and the data will be divided into two categories, namely the category of slang and non-slang. This study aims to compare two classification algorithms, namely Naïve Bayes and Decision Tree to see which algorithm is more effective in classifying how many social media users use slang in commenting based on the dataset we have collected, so that results are obtained to see how high the percentage of usage is. Indonesian people's slang in commenting on social media.

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How to Cite
Dharma, A., Aditya Calderon Naibaho, Lolo Mulatua Bancin and Alhoi Andrew Jefferson (2022) “Classification Of Indonesian Slang Using Naïve Bayes And Decision Tree Methods On Social Media”, Jurnal Mantik, 6(2), pp. 1792-1798. doi: 10.35335/mantik.v6i2.2647.
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