Analisis Sentimen terhadap Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) Level 3 berdasarkan Data Twitter menggunakan Algoritma Naive Bayes - Annisa Alifia; Imam Cholissodin; Putra Pandu Adikara (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2023)
The rapid development of technology has made it easier for people to express their aspirations. These aspirations can be channeled through social media which is currently increasingly popular among the public. One of the social media that is often used by Indonesian citizens is Twitter. In February 2022, Community Activities Restrictions Enforcement Level 3 had become a trending topic on Twitter, which indicated that the increase in the level elicited various responses from the public. Community Activities Restrictions Enforcement (CARE) is one of the policies that the government has implemented in tackling Covid cases in Indonesia. Public opinion regarding this issue will generate various sentiments that can be analyzed. In this study, sentiment analysis will be carried out on public opinion regarding the increase in Community Activities Restrictions Enforcement to level 3 using the Multinomial Naive Bayes algorithm. The process consists of data pre-processing, word weighting with Raw Term Frequency, training and testing of the Naive Bayes model which later the accuracy results will be calculated using the K-Fold Cross Validation of 5 folds. This study produces an average accuracy of 0.78 with the addition of stop words and data normalization. This accuracy does not create much difference without using stopwords and data normalization with an accuracy of 0.79. The addition of stopwords and data normalization still does not produce a significant difference.