Analisis Sentimen Terhadap Program Makan Bergizi Gratis Pada Media Sosial X Menggunakan Metode Naive Bayes Classifier

Abstract

The rapid development of information and communication technology has positioned social media as a major platform for expressing public opinions on government policies, including the
Free Nutritious Meal Program (MBG) launched in January 2025. This study aimed to analyze public sentiment toward the program using the Naïve Bayes Classifier. Secondary data were obtained from user posts on platform X through a data crawling technique and processed using cleaning, case folding, tokenizing, stopword removal, and stemming. Sentiment classification was conducted into positive, negative, and neutral categories, and the Synthetic Minority Over-sampling Technique (SMOTE) was applied to address data imbalance. Model performance was evaluated using accuracy, precision, recall, and F1- score. The results showed 407 positive comments, 383 negative comments, and 304 neutral comments. The best model with parameter α=0.3 achieved an accuracy of 83.76%. Overall, public sentiment toward the MBG Program tended to be positive, although continuous
evaluation remained necessary.