ANALISIS SENTIMEN TERHADAP ULASAN KEPUASAN PELANGGANPADA MARKETPLACE TOKOPEDIA DI JEJARING SOSIAL TWITTERMENGGUNAKAN ALGORITMA NAIVE BAYES - Muhammad Abi Nurhakim, (2021)
Consumer reviews about shopping satisfaction in the marketplace are valuable information and can be processed properly. This information can be used to obtain product and service evaluations by both consumers and sellers or marketplaces by analyzing the shopping experience reviews through the Twitter social network in order to obtain the necessary information. Review analysis activities cannot be enough just to look at the number of ratings, but it is necessary to look at the entire content of the review to be able to find out the broader and general meaning of the review. If a small amount can be done manually, but to see a large number of reviews, a system is needed to be able to analyze more effectively and make it easier to understand the purpose of the review. In this study using the Naïve Bayes classification method which is divided into 2 classes, namely positive and negative. The results of the classification using the Naïve Bayes algorithm obtained an accuracy of 79.02%, precision of 80.30%, recall of 77.94% and specificity of 80.15%.