Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter. © 2022 IEEE.

The Impact of the COVID-19 Pandemic in Indonesia (Face to face versus Online Learning)

Covid-19 pandemic is an international disaster that is experienced by almost all countries in the world. This has an impact on all lines of the life of each country. Among them is the education sector. Aside from efforts to solve this co-19 problem, the state must continue to maintain the stability and sustainability of the learning process that is the right of all citizens. Indonesia experienced the same thing. face to face learning "shock" and immediately take the fastest action by utilizing existing technology, but not all of them are ready. Using survey methods and adopting the theories of Delon and McLean, this study aims to determine the readiness of organizers, lectures, and students for current conditions, their readiness in undergoing the learning process while maintaining the quality of education and user satisfaction (instructors and students) towards learning. The results of this study prove that we all tend to be unprepared but strangely, on the other hand, the fact is that the positive things from this pandemic prove that education practitioners in Indonesia are better prepared by online learning because they are more comfortable and satisfied with online learning while supported by the government and a good system (96% of respondents) compared to face to face (4% of respondents).