| Abstrakt: |
During the Covid-19 pandemic, many opinions were voiced by the public using social media platforms, one of which was using Twitter. By analyzing the opinion, it can be classified that the opinion is a positive opinion which is a support opinion, or a negative opinion which is a derogatory opinion. But there is another opinion called sarcasm opinion. In this study, analyzing the sarcasm opinions contained in twiiter. For sentiment analysis using unigram, select k-best, and TF-IDF, for classification, namely Naive Bayes. Whereas for the classification of sarcasm using the Random Forest Classifier which has 4 features, namely, Sentiment-relate, Puncuation-relate, Lexcial and Syntatic, and Pattern-relare, for classification using the Decission tree. The results in this study on the training data obtained an accuracy rate of 76%, and for the test data obtained an accuracy rate of 92%. [ABSTRACT FROM AUTHOR] |
