Twitter User Sentiment Analysis For RUU Omnibus Law Using Convolutional Neural Network

The general function of social media is for online interaction with many people. Moreover, social media have functions for sharing information, discussing, and giving an opinion media about some topics that a lot of people talk about, one of that media is Twitter. An atopic will show many opinions and different responses from everyone. This study was for making an analysis of opinion from social media Twitter users about the Rancangan Undang-Undang (RUU) Omnibuslaw topic using a Convolutional Neural Network method which is one of the Deep Learning methods. This study has done a sentiment analysis with opinion data from many different people through the tweet they make, Preprocessing and weighting are done using Word2vec which give 84% result accuracy of an algorithm from 10-time testing. Based on 2.820 tweet data, the result is 1.320 data of positive sentiment, and 1.500 data of negative responses for the RUU Omnibuslaw topic in Indonesia.