SENTIMENT ANALYSIS OF PUBLIC RESPONSE TO GREEN TECHNOLOGY AT X USING NAÏVE BAYES METHOD - Mashun, Yulialda; Aristamy, I Gusti Ayu Agung Mas; Putri, Ni Wayan Suardiati; Sandhiyasa, I Made Subrata; Willdahlia, Ayu Gede (Proceeding International Conference on Information Technology, Multimedia, Architecture, Design, and E-Business, 2024)
The development of IKN as a green technology city has sparked significant public discourse, particularly on social media platform X. This research aims to analyze public sentiment towards this initiative using a Naïve Bayes classifier. By examining 866 posts and comments from January 2022 to April 2024, tagged with the keyword "green technology". TextBlob was employed to label the data, while a multinomial Naïve Bayes classifier was used for sentiment classification. The results indicate a predominantly negative sentiment, with 59.20% of the data categorized as negative and 40.80% as positive. A confusion matrix analysis of the test data yielded an accuracy of 76%, precision in class 0 of 78%, while in class 1 of 73%, recall in class 0 of 83%, while in class 1 of 66%, F1-score in class 0 of 81%, while in class 1 of 70%. These findings suggest that while there is public support for green technology, a significant portion of the population remains skeptical or concerned about its implementation.