Sentiment Analysis to analyze Vaccine Enthusiasm in Indonesia on Twitter Social Media

M. Khairul Anam; Rahmaddeni; Muhammad Bambang Firdaus; Hadi Asnal; Hamdani

doi:10.33372/jaia.v1i2.794

M. Khairul Anam STMIK Amik Riau
Rahmaddeni
Muhammad Bambang Firdaus Mulawarman University
Hadi Asnal
Hamdani

DOI: https://doi.org/10.33372/jaia.v1i2.794

Keywords: Vaccines, Tweet, Sentiment Analysis, Naïve bayes

Abstract

Vaccines are one way to prevent the coronavirus from entering the human body, although it is not 100% accurate. However, the implementation of vaccination in Indonesia is still controversial. People give their opinions directly or through social media such as Twitter. Retrieval of tweets using the Twitter API and using python. The data obtained is then preprocessed using case folding, cleaning, tokenizing, filtering, and stemming. After that, the model was evaluated using the Naive Bayes method. Naïve Bayes is a classification method that can predict the probability of a class to produce decisions based on learning data. Currently, nave Bayes is one of the methods to find accuracy in sentiment analysis that is often used and is the best. The results of this study obtained an accuracy of 79%.

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