Sentiment Analysis of the Covid-19 Virus Infection in Indonesian Public Transportation on Twitter Data: A Case Study of Commuter Line Passengers

Abstract

The appearance of the Covid-19 virus in early 2020 became a frightening pandemic for the world, including Indonesia. The infection of the Covid-19 virus was rapid because of its transmission can be through human contact. This condition causes worrying in society. Besides, these worrying also occurs in the passenger of public transportation, especially the commuter line. Passengers in large numbers and push each other will cause worry if commuter line passengers will transmit the Covid-19 virus to the commuter line. Many passengers write their opinions about the transmission of the Covid-19 pandemic on social media Twitter. This causes various opinions that can be positive, negative, or even neutral. Therefore, to see the opinions on commuter line passengers, a research was made to analyze the sentiment of the Covid-19 transmission to commuter line passengers. This research was implemented using a comparison of 2 methods, Naïve Bayes outperformed the Decision Tree with an accuracy of 73.59%. Furthermore, the result of sentiment analysis was a positive classification compared to the other 2 classes.