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

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

Jurnal Mantik
Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)

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.