Analisis Sentimen Terhadap Permendikbud Ristek Nomor 30 Tahun 2021 pada Media Sosia Twitter Menggunakan Metode Lexicon-Based dan Multinomial Naïve Bayes

Regulation of the Minister Education, Culture, Research, and Technology (Permendikbud Ristek) Number 30 2021 was launched as a form government efforts in context preventing handling sexual violence universities. However, it turns out that this regulation has generated various reactions from community, most them support while others reject ratification regulation. Technological developments occur today encourage people to write their opinions on social media, one which is Twitter. Tweets discussing rule can be used gauge public sentiment. considering number tweets, classification process will difficult do manually, so requires computational system automatically classify sentiments existing tweets. From these problems, designed perform sentiment analysis using lexicon-based method Multinomial Naïve Bayes. The results measurement useful data material for Ministry Education Research making decisions regarding rule. purpose research measure value accuracy, precision, recall, f-measure Bayes methods. obtained dataset 470 are accuracy 71.28%, precision 70.10%, recall 78%, 74.29%.