ANALISIS SENTIMEN ASISTENSI MENGAJAR PADA MEDIA SOSIAL TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER (NBC)

ANDRI, TRI GUSTAMI (2023) ANALISIS SENTIMEN ASISTENSI MENGAJAR PADA MEDIA SOSIAL TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER (NBC). S1 thesis, Universitas Muhammadiyah Purwokerto.

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Abstract

Teaching assistance is one of the Merdeka Belajar Kampus Merdeka (MBKM) programs which aims to improve studens skills and knowledge, as well as to prepare studens for the wold of work. Some people express their opinions about teaching assistance thourg social media Twitter. This opinion can be used as material for sentiment analysis which aims to find out public opinion on teaching assistance on twitter social media. This research will classify these opinions into there classes, namely positive, negative and neutral. The classification in this study uses the naïve bayes Classifier (NBC) method which produces an accuracy of 82%, the highest precision is 84%, the highest recall is 95% and the highest f1-score is 89%.

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