Analisis Sentimen Media Sosial Twiiter terhadap RUU Omnibus Law dengan Metode Naive Bayes dan Particle Swarm Optimization
Social media is the most popular platform by the Indonesian people, starting from Facebook, Instagram and Twitter. Twitter is one of the most widely used social media, both for interacting with other people or looking for information or news that is trending topics, quickly various news or information spreads on Twitter such as issues that are currently trending, namely the Omnibus Law. , various responses given by twitter users regarding this policy that has been approved by the government. In this study, to classify the sentiments of the Indonesian people regarding the issue of Omnibus Law using the method Naïve Bayes and Particle Swarm Optimization (PSO) and divided into two test scenarios, the use of theAlgorithm Particle Swarm Optimization on Naive Bayes aims to optimize the accuracy results. The results obtained when using Naive Bayes based on Particle Swarm Optimization (PSO) are better than Naive Bayes. The best accuracy results are in scenario three with split 90% - 10% data using Naïve Bayes to get 85% results and using Naïve Bayes based on Particle Swarm Optimization the accuracy results change to higher 4% get 91% results, the amount in doing the split data is very influential on the results of the classification carried out. The response from the public is in the form of negative sentiment towards the Omnibus Law Bill.