ANALISIS SENTIMEN SERIKAT PEKERJA PERTAMINA TOLAK AHOK PADA MEDIA SOSIAL YOUTUBE MENGGUNAKAN ALGORITMA NAIVE BAYES - Muhammad Soekarno Putra Putra; Sri Dharma Wati; Imam Solikin (LPPM Sekolah Tinggi Teknologi Pagar Alam, 2021)
In this study, an analysis of public sentiment will be carried out on the news of the Pertamina workers union rejecting Ahok which was revealed through the social media network youtube on the KompasTV channel. On the news there were about 25000 comments containing harsh words and even hate speech, this news attracted a lot of comments, there were those who praised, criticized and insulted. Sentiment analysis is the process of classifying textual documents into two classes, namely positive and negative sentiment classes. The data used in this study amounted to 1000 comments consisting of 1000 training data or training data and 300 test data or testing data, the classification method used in this study was naive bayes. In this study, data collection using Rstudio tools and processed using the rapidminer studio tools, and get the accuracy of 98.00%. From some of the data that has been tested, there are some data that are predicted to be neutral, positive data and data that are predicted to be negative. From the precision class, the neutral prediction has a class value of 100.00%, the positive prediction has a class value of 80.00% and the negative prediction has a precision class value of 66.67%.