Analisis Sentimen Pembelajaran Daring Dimasa Pandemi Covid-19 Pada Pengguna Twitter Menggunakan Metode Naïve Bayes

Haironi, Muh Rezha (2022) Analisis Sentimen Pembelajaran Daring Dimasa Pandemi Covid-19 Pada Pengguna Twitter Menggunakan Metode Naïve Bayes. Diploma thesis, Politeknik Negeri Jember.

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Abstract

Education in Indonesia is also one of the areas affected by the Covid-19 pandemic. These limitations certainly have an impact on the learning process in Indonesia, especially for the regular learning model, namely face-to-face. With restrictions on interaction, the Ministry of Education in Indonesia also issued a policy, namely to remodel schools and replace the Teaching and Learning process using an online system. Various distance learning media are tried and used. Facilities used as online learning media include e-learning, among others, the zoom application, google classroom, youtube, and WhatsApp social media. These facilities are used optimally, as a medium for conducting learning like in class. By using this media, apart from being bored because you can't meet friends, you can't interact directly with lectures, so it's not fun. Differences in infrastructure, connection quality, devices used, and the high cost of internet quotas are the main obstacles. The sudden change from face-to-face learning to online learning on a large scale caused various responses or opinions in the community. Evaluation of the system on the system made based on the algorithm used in this study, namely the Naïve Bayes Classifier, in classifying sentiment analysis on online learning topics on Twitter social media, the results of accuracy, precision, recall and FMeasure are as follows 64.39 %, 66%, 62.08%, and 63.98%

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