Sentiment Analysis Of Public Opinions On The Effectiveness Of Online Learning Using Naïve Bayes Algorithm - Ratna Pinka Baptis Dakhi; Achmad Maezar Bayu Aji (Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta, 2022)
Covid-19 was declared a global pandemic by the World Health Organization (World Health Organization) on March 11, 2020. This has resulted in the government urging the public not to carry out activities outside the home which is an effort to break the chain of spreading Covid-19. Activities that were suddenly stopped had a negative impact on the community. Starting from the decline in economic growth to the lagging of students in studying. The Covid-19 pandemic has had an impact on various perspectives of human life today, especially in the field of education. So that the teaching and learning process continues. All students are required to study at home online or online. However, online learning raises pros and cons among the public, so research needs to be done to analyze public sentiment about online learning and find out the effectiveness of online learning during the Covid-19 pandemic by utilizing Twitter as a source of data to be researched. Based on the results of the analysis of public opinion sentiment about online learning using the Naïve Bayes Classifier algorithm with Rapidminer as the software used in data processing, the accuracy value is 60.00% with 65.67% precision and 53.30% recall