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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer)
Sabar Sautomo
STMIK Nusa Mandiri
Computer Science & IT

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SENTIMENT ANALYSIS DUE TO "MUDIK" PROHIBITED OF COVID-19 THROUGH TWITTER Sabar Sautomo; Noor Hafidz; Yuni Eka Achyani; Windu Gata
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1192.563 KB) | DOI: 10.33480/jitk.v6i1.1357

Abstract

“Mudik” is a habit every year for the people of Indonesia to return to their hometowns before the Eid. The existence of the Corona Virus pandemic (COVID-19) hit all over the world, including Indonesia, resulting in a ban from the government to do Mudik. Social media such as Twitter is often used as an expression of some people in commenting on something like the ban on Mudik. Comments on Twitter that are often known as tweets can be used as material for sentiment analysis. However, it is not easy to do sentiment analysis on Twitter, especially comments in Indonesian, because the text is not structured. This study uses data from Indonesian-language tweets containing the word "Mudik," the algorithm model used in this study, Naïve Bayes Classifier and Support Vector Machine, is compared to get accuracy, precision, recall, and F1-score values. From this research, it was concluded that the Naïve Bayes algorithm and Support Vector Machine performed well enough to predict the sentiment of tweets about Mudik on Twitter social media. Naïve Bayes with an accuracy of 82% and f1-score 0.8, while Support Vector Machine with an accuracy of 87% and f1-score 0.87.
Co-Authors Noor Hafidz Windu Gata Yuni Eka Achyani, Yuni Eka