Analisis Sentimen Masyarakat Terhadap Virus Corona Berdasarkan Opini Masyarakat Menggunakan Metode Naïve Bayes Classifier

Abstract

The current use of social media is not only to communicate between friends, but is often also used as a means to convey an aspiration to the community, especially the Indonesian people regarding government issues, or problems related to health and other problems. One of the uses of this social media is to use it as a means of conveying digital aspirations, such as some slogans that are used as hashtags, namely #dirumahaja #lockdown, #usemasker, #protocol, #imun, #vaccine. From the slogan used as a hashtag, researchers are interested in conducting research on how much negative sentiment and positive sentiment there are, using the Naïve Bayes Classifier method, which is a machine learning method that uses probability calculations. The basic concept used by Nave Bayes is the Bayes Classifier Theorem, which is a theorem in statistics to calculate probability, the Bayes Optimal Classifier calculates the probability of one class from each existing attribute group, and determines which class is the most optimal, as for the advantages of using Nave Bayes Classifier in document classification can be viewed from the process that takes action based on existing data to provide solutions to these sentiments.