Analisis Sentimen Pengguna Sosial Media Twitter Terhadap Perokok Di Indonesia
DOI:
https://doi.org/10.33022/ijcs.v12i1.3154Keywords:
Sentiment Analysis, Smokers, Naive Bayes, Support Vector Machine, Decision TreeAbstract
One of the tools web users use to access, share, and discuss subjects of interest is social media. One social networking site, Twitter, is often used in real time to communicate this. Due to its significant negative impacts on both health and the economy, smoking is still a topic of regular debate and debate in Indonesia. This research was conducted to assess sentiment towards smokers and differentiate between positive and negative emotions. The data used in this study were obtained by crawling the Twitter social media network. Three Bayes techniques (NB), Support Vector Machine (SVM), and Logistic Regression are used in this study. In this study, 40.25% of Twitter users agreed with the existence of smokers in Indonesia, while 59.74% disagreed. The Naive Bayes method was used in this study, giving the highest accuracy value = 62.1% using 60% training data and 40% test data.
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