Analisis Sentimen Pembelajaran Daring Pada Twitter di Masa Pandemi COVID-19 Menggunakan Metode Naïve Bayes

The WHO announced that more than 52 million people tested positive for Covid-19, and 1.2 died in the second week of November 2020. Meanwhile, Indonesia recorded 463 thousand individuals with 15,148 deaths were confirmed positive. Strategy against pandemics by incorporating socialization. However, learning was initially bold as a technique became controversial due to briefness adaptation process. wide continuum social reactions has resulted sudden transition from face-to-face on large scale. This research focuses public opinion online during Indonesian COVID-19 pandemic early analysis carried out Twitter mining document-based text interpreted using Naïve Bayes algorithm. results show sentiment 30 percent, negative 69 neutral 1 percent over period. Due community dissatisfaction about learning, significant amount is created. Some tweets indicate disappointment words' stress 'and' lazy 'in conversation being high-frequency words.