Comparison of Naïve Bayes Classifier Algorithm and Support Vector Machine Classification for the Sport Event at X Platform

The Indonesian U-23 national team managed to qualify for the semifinals in the AFC U-23 event in Qatar even though they failed to win first place against Uzbekistan and third place against Iraq. On social media Twitter (x), Indonesia’s match at AFC U-23 as a new debutant became a hot topic of conversation among Indonesian netizens. Various groups of people support it through their opinions. Several opinions from the public on Twitter (X) will be used as research data for sentiment analysis regarding the AFC U-23 event. This research uses the Naïve Bayes Classifier and Support Vector Machine (SVM) methods which are expected to have a good level of accuracy. Based on the research results, it was found that different levels of accuracy from several data set divisions were divided into 3 (three) types, namely 80:20, 90:10 and 75:25. The use of the Naïve Bayes method produced a higher level of accuracy than the Support Vector method. Machine (SVM) with accuracy results in the data (80:20) for Naïve Bayes achieved an accuracy of 97.83% while for the Support Vector Machine it achieved an accuracy of 97.29%. For the data (90:10) the Naïve Bayes method reached 96.77% while for the Support Vector Machine it was 95.69% and for the data (75:25) the Naïve Bayes method got an accuracy value of 97.83% and the Support Vector Machine accuracy value was 97.83% and produced sentiment. analysis is classified as positive.