Analisis Sentimen Masyarakat Terhadap Pandemi Covid-19 Pada Sosial Media Menggunakan Naïve Bayes Clasifier

Abstract


 
 
 Social Media is an application internet based of communication. Twitter is one tool that Internet users frequently utilize. Twitter is one tool that Internet users frequently utilize., Twitter is a website that offers microblogging services so that users can communicate ideas, opinions, or just their daily lives through brief writings called Tweets. Social media is a communication tool that Internet users are currently using in large numbers. Tweets from Twitter users cover a wide range of topics, and from these tweets, data can be extracted for sentiment analysis, which can provide information to a variety of parties. The purpose of this project is to develop a system for sentiment analysis that can produce data and information in the form of positive sentiment, negative sentiment, and neutral sentiment. The Nave Bayes Classifier technique is used to categorize feelings. This system receives input in the form of public tweets on the Covid-19 Pandemic. Data visualizations of positive, negative, and neutral sentiment are produced by this system as its output. The Public Sentiment Analysis System with the Nave Bayes Classifier Algorithm can automatically do sentiment analysis with an accuracy of 70% when classifying a tweet using the Nave Bayes Classifier approach. The analysis's findings are presented in tabular form and visually using word clouds and diagrams.