<![CDATA[The Free Nutritious Meal Program introduced by President-elect Prabowo Subianto has garnered public attention and sparked a variety of responses, both positive and negative. The Free Nutritious Meal Program (MBG) is part of the Indonesian government's policy aimed at improving public nutrition, the welfare of school-going children, and the quality of human resources from an early age. However, during its implementation, several problems have emerged, including cases of food poisoning in several areas. Understanding public perception of these problems is important in order to evaluate the program's success. This study aims to analyze public sentiment towards the MBG program on social media "X" using three algorithms: SVM, K-Nearest Neighbor, and Naive Bayes. Data obtained through the crawling process is then processed with a preprocessing stage and sentiment classification into two categories: positive and negative. The evaluation results show that the Naive Bayes model has a higher accuracy than the other models, namely 86.70% accuracy, 86.10% precision, 86.70% recall, and 83.70% F1 score. The analysis shows that the number of negative sentiments is greater than positive sentiments. The results of this study can be used by the government to improve the socialization and implementation of programs to ensure greater public acceptance, and to emphasize the importance of implementing strict food safety standards, from raw material procurement to processing.]]>
Copyrights © 2025
