Analysis Classification Opinion of Policy Government Announces Cabinet Reshuffle on YouTube Comments Using 1D Convolutional Neural Networks

摘要

YouTube social media has been equipped with a comment column facility so that viewers can comment on YouTube video information in the form of comments or opinions that lead to likes, dislikes, and neutrality. With the increase in the number of viewers, there were also more comments on various writing kinds, both symbolic and numeric. The author wants to take these comments into useful information using sentiment analysis using the 1D Convolutional Neural Networks method. From the results of this study, classification can be done very well with the CNN model and accuracy by using variations of epoch 10, 30, 150, and 300 with the best results of 100%, loss: 1.6%. This study also compared the classification reports for precision, f1-score recall, and accuracy with the Naïve Bayes 93% and CNN methods, with an accuracy of 96%.