Andraini, Fitri2022-11-142022-11-142022-07PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/10737Sentiment analysis is one of the sciences in Text Mining which is used to classify text documents in the form of public opinion. The text document used in this study comes from Twitter using three positive, negative, and neutral labels. The method used was the Support Vector Machine. This study used 2000 data using two data test scenarios, namely, Split Validation and Cross Validation. Testing data with Split Validation was divided into 4 variations, namely, 50%:50%, 70%:30%, 80%:20%, and 90%:10%, while testing data with Cross Validation was divided into 10 tests. The highest accuracy result used the Split Validation test laid in a comparison of 90%: 10%, which is 83.5%, while data testing with Cross Validation had the highest accuracy at K-Fold 7 of 86.0%.enText MiningSupport Vector MachineSplit ValidationCross ValidationK-foldK-fold Cross ValidationArticle