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Abstract
The Government of the Republic of Indonesia in an effort to handle the handling of the spread of Covid-19 in Indonesia has a plan to implement a covid-19 vaccination for the Indonesian people in late 2020. However, many people are still confused about its safety, side effects and how to get it. The collection of response data and Indonesian public opinion on the COVID-19 vaccine policy was carried out using web scraping techniques on Twitter social media in the form of tweets. The activity of classifying tweets or sentiment analysis in this study was carried out using the lexicon-based method or positive-negative dictionary-based. Referring to the research conducted previously, the activity of grouping public opinion on social media twitter was carried out using the Latent Dirichlet Allocation (LDA) model. Positive sentiment is greater than negative sentiment regarding the Covid-19 vaccine policy. The topics that stick out and are popular in the conversations of social twitter users are the topic of education on the function of vaccines, hopes, and public trust in vaccination. Another popular topic is netizen notifications regarding activities he has participated in.
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Copyright (c) 2022 Akhmad Rizal Dzikrillah, Dyvia Oliviani Dyvia Oliviani
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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