<![CDATA[This research employs the Support Vector Machine algorithm to classify sentiment in comments on the X, Youtube, and Tiktok platforms regarding the use of BPA-free water gallons in Indonesia. From a total of 1200 data points, post-labeling, 772 data points were obtained, with 552 classified as positive and 220 as negative. The experimental results reveal that SVM achieves an accuracy of 96.15%, while Naïve Bayes achieves an accuracy of 84.55%. These findings indicate that SVM is effective in classifying sentiment with a high accuracy rate, providing valuable insights for manufacturers, government entities, and consumers regarding the use of BPA in water gallons in Indonesia. This study contributes to a better understanding of the role of social media in shaping public opinion and policies related to environmental and health issues.]]>
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