Sentiment Analysis Vaksinasi Covid-19 Pada Media Sosial Twitter Menggunakan Mutinomial Naïve Bayes

Pratama, Eilham Wahyu (2022) Sentiment Analysis Vaksinasi Covid-19 Pada Media Sosial Twitter Menggunakan Mutinomial Naïve Bayes. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

Development of Information Technology that develops in the current era of globalization serves to simplify, accelerate, and provide other alternatives for communication options. One of the Developments in Information Technology is social media. Social media has become one of the media that provides the widest possible space for each individual to share and create. As a result of the existence of social media, it directly causes changes in society. The fact is that behind the many positive sides, social media also has a negative side on social media platforms such as Twitter, where every day there are always updated trending topics so that users can see what is being discussed that day. Thus users are free to express their responses regarding the covid-19 vaccination. There are several users who strongly agree with this and there are also individuals who take advantage of this condition by inciting other users to think negatively regarding the Covid-19 vaccination. Therefore we need a technology to be able to detect the percentage level of pros and cons by utilizing the TF-IDF (Term Frequency — Inverse Document Frequency) technique. Evaluation of the system on the system based on the algorithm used in this study, namely Multinomial Naïve Bayes, in classifying sentiment analysis on the topic of covid-19 vaccination on social media twitter has results of accuracy, precision, recall and F-Measure respectively as follows: ,97%, 45%, 50%, and 47.36%.

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