ANALISA SENTIMEN PENGGUNA TERHADAP KEBIJAKAN BARU WHATSAPP MENGGUNAKAN NAIVE BAYES CLASSIFIER DAN SUPPORT VECTOR MACHINE

Abstract

This study applies the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms in classifying WhatsApp user review data to determine the percentage of user sentiment towards the whatsapp’s new privacy policy and to compare the performance of the two algorithms. This study uses 760 data with the distribution of training and testing data, namely 90%:10%, 70%:30%, 50%:50%, 30%:70%, and 10%:90%. The results showed that there were 338 positive reviews and 422 negative reviews, so it can be concluded that the trend of user sentiment towards the whatsapp’s new privacy policy was negative with a percentage of 56%. The results of the confusion matrix test show that the highest accuracy value is obtained in the first test with a data ratio of 90%:10%. The NBC method has an accuracy of 92.11% while the SVM method has an accuracy of 96.05%, it can be said that the SVM method has a better performance than the NBC method in classifying whatsapp user review data.