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All Journal UNP Journal of Statistics and Data Science
Husni, Nabila
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Analisis Sentimen Program MSIB pada Aplikasi X (Twitter) Menggunakan Algoritma Naïve Bayes Husni, Nabila; Dodi Vionanda; Nur Leli; Syafriandi Syafriandi
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss2/361

Abstract

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.
Co-Authors Dodi Vionanda Nur Leli Syafriandi Syafriandi