Sentiment Analysis of the MSIB Program on Application X (Twitter) Using the Naïve Bayes Algorithm
DOI:
https://doi.org/10.24036/ujsds/vol3-iss2/361Keywords:
MSIB, Naïve Bayes, Sentiment Analysis, Web Scraping, XAbstract
Certified Internships and Independent Studies (MSIB) is one of the programs of the Independent Learning-Independent Campus (MBKM) curriculum as a policy of the Kemendikbudristek. A government policy, especially in terms of education, will of course give rise to stigmas or feedback from the public regarding the policy. This research aims to find out public opinion regarding the MSIB program in the X (Twitter) application by sentiment analysis using the Naive Bayes Classifier algorithm. From this analysis, it was found that 84.6% of reviews had positive sentiments, while 16.4% of reviews had negative sentiments. Evaluation using the Naïve Bayes Classifier model shows that this model succeeded in classifying 85% of all data correctly, showing quite good performance in classifying the sentiment of these reviews.
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Copyright (c) 2025 Nabila Husni, Dodi Vionanda, Nur Leli, Syafriandi Syafriandi

This work is licensed under a Creative Commons Attribution 4.0 International License.