SENTIMENT ANALYSIS OF PUBLIC FIGURE USING NAÏVE BAYESIAN CLASSIFICATION ON TWITTER APPLICATION
https://doi.org/10.36342/teika.v7i1.2218
Keywords:
Sentiment Analysis, Naïve bayes, Naïve Bayes Classification, TwitterAbstract
Social media has provided a variety of information, especially content that is subjective or reflects the opinions of people who write. Today more and more people express their opinions or opinions on community leaders such as regional leaders, officials, influential people, and so on. Social media has provided a variety of information, especially content that is subjective or reflects the opinions of people who write.
Today more and more people express their opinions or opinions on community leaders such as regional leaders, officials, influential people, and so on. Sentiment analysis on the Twitter social media application there are weaknesses in the words contained in the sentence uploaded by the application user. In this case the object of the research was carried out to Ridwan Kamil with Sentiment Analysis from the people. Based on the research conducted, it was concluded that 59 training data had an accuracy of 81.3559%, and the results obtained from testing data were: 1. There were 3 data that were truly classified as having neutral sentiments, 2. There were 7 data classified really have positive sentiment, 3. And there are 2 data that really have negative sentiment.
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