Analisis Sentiment Masyarakat terhadap Kasus Covid-19 pada Media Sosial Youtube dengan Metode Naive bayes - Ahmadi, Muhammad Iqbal; Gustian, Dudih; Sembiring, Falentino (J-SAKTI (Jurnal Sains Komputer dan Informatika), 2021)
The development of Covid-19 cases in Indonesia continues to increase. with the continued increase in these cases causing panic among the public regarding the presence or absence of this corona virus, in the midst of this condition an effective and efficient communication pattern is needed in providing education and information about this corona virus, for example with social media Youtube. Many people's responses to this news are expressed in the comments column. Therefore, a sentiment analysis model is needed to classify public comments into Positive, Negative and neutral. In this study, the Naive bayes method is used to build a sentiment analysis model for public responses about the news on the development of the Covid-19 case on the Youtube page, precisely on the KompasTV Chanel. Accuracy is 74% with the number of comments Positive 361, Negative 800 and neutral 490.