ANALISIS SENTIMEN DATA ULASAN APLIKASI RUANGGURU PADA SITUS GOOGLE PLAY MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER DENGAN NORMALISASI KATA LEVENSHTEIN DISTANCE

Abstract

One form of technological development in education is the increasing number of online based learning. More than that, during this period of Covid-19 pandemic distance education was tried by the government that requires learning are done online. The online learning application that is the implementation of this technological development continues to show its existence. Many non-formal educational companies are available, one of which is the Ruangguru, getting a nickname as a number one learning application requires the Ruangguru to continue and improve the performance. Users of the Ruangguru application can communicate a response to Ruangguru through the review feature available on the google play site. The reviews that have been written can be analyzed how the user sentiment is whether positive or negative using Multinomial Naïve Bayes. This method is used because it is easy to use with simple structures and gives high accuracy values. The model will be selected using 10-fold cross validation method to get the model with the best accuracy. The normalization phase of words was also perfected using Levenshtein Distance method that was proven to add accuracy value. Performance result using Multinomial Naïve Bayes by adding Levenshtein Distance method to fix the words gives an average accuracy value of 88,20% with the 8th fold as the fold with the best accuracy value of 94%.