Sentiment analysis of distance learning policy during the Covid-19 pandemic using naïve bayes algorithm

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Parasian D. P. Silitonga, Darsono Nababan, Emerson P. Malau, Alex Rikki

2023 AIP Conference Proceedings Vol. 2798 Issue 1 Conference paper Cited by 0 Quartile

Abstract

Sentiment analysis is the interpretation and classification of users' emotions (positive, negative, neutral) about a subject in text data using text analysis Comments and opinions, especially those contained in social media, are a source of data that can be used to measure the level of popularity of a program or product launched. Social media is a means to convey aspirations directly, but every aspiration is from social media users. Everyone who expresses opinions on social media contains positive, negative, and neutral sentiments. The implementation of the Ministry of Education and Culture's policy on the implementation of distance learning policies during the pandemic COVID-19 received various responses from the people of Indonesia. neutral as many as 894 comments, then 52 comments with negative sentiment, and 32 comments with positive sentiment with an accuracy value of 98.79%. © 2023 Author(s).

Affiliations

Faculty of Computer Science, Universitas Katolik Santo Thomas, Medan, Indonesia; Department of Information and Technology, University of Timor, Kefamenanu, Indonesia