Sentiment Analysis on Tweets of Kanjuruhan Tragedy Using Deep Learning IndoBERTweet

 (*)Adhyaksa Diffa Maulana Mail (Telkom University, Bandung, Indonesia)
 Kemas Muslim Lhaksmana (Telkom University, Bandung, Indonesia)

(*) Corresponding Author

Submitted: April 26, 2023; Published: July 23, 2023


The incident that occurred in Indonesian football at the Kanjuruhan Stadium was caused by unscrupulous supporters who entered the field and unscrupulous officers who fired tear gas into the stands. With this incident, many responses and opinions were given by the Indonesian people through social media Twitter in the form of positive, negative, and neutral opinions. This difference in opinion occurred because of the many victims who died or were injured, with many supporters who did not like the actions taken by the authorities during the riots. With this incident, the government must make decisions to ease the concerns of the community. Therefore, research will be conducted to analyze the sentiment of public opinion regarding the Kanjuruhan tragedy using the IndoBERTweet method with a comparison using naive Bayes. The results of this study using the IndoBERTweet method get better results than naive Bayes method. With the results of the IndoBERTweet method 88% accuracy, 82% precision value, 85% recall value, and 84% f1-score value, naive the Naive Bayes results are 62% accuracy, 59% Precision Value, 61% Recall Value, and f1-Score of 59%.


Kanjuruhan; Sentiment Analysis; Twitter; IndoBERTweet; Naïve

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