Sentiment Analysis Of Waste Management In Bandung With Naïve Bayes Algorithm

Sentiment analysis of waste management in Bandung and its surrounding areas is the focus of this research. Previous research has shown that many respondents are dissatisfied with the city's waste management practices and criticize inadequate services. Therefore, further sentiment analysis is needed to understand the public's view of waste management in Bandung. This study obtained opinion data from social media sites like Twitter and Instagram. We chose the Multinomial Naive Bayes method as the analytical model for the text classifier and implemented it using the CRISP-DM framework. The analysis results show the model's accuracy in predicting sentiment is 0.75. In addition, the results of sentiment analysis using the N-Gram approach found that many people still are unaware of waste management in Bandung by littering. This research helps us understand the waste management issue in Bandung and its surroundings. The government, related institutions, and the public can take advantage of the sentiment analysis findings as a reminder and evaluation of waste management problems in Bandung.