Telkom University Slogan Analysis on YouTube Using Naïve Bayes

Abstract

YouTube is often used in public and private universities as branding for first-year students. YouTube facilitates users to interact by giving likes or dislikes, adding viewers to the video, and responding to videos through comment pages that can analyze by public feedback for branding. In doing branding, many alumni and college students discuss Telkom University as the best private university in content uploaded on YouTube. That can trigger the public to give positive, negative, or neutral comments to Telkom University. In this research, sentiment analysis focuses on the scientific context of branding the slogan "Number 1 Best Private University" to find out the perspectives and opinions of the public that can be used as evaluation material for the university to improve its reputation. Dataset takes from user opinions on YouTube regarding content that discusses Telkom University's branding slogan using the Term Frequency–Inverse Document Frequency (TF-IDF) feature extraction and Naïve Bayes as a classification. The final results of this research show that the ratio of 90:10 normalized then combined with the unigram-bigram token and Naïve Bayes with alpha 0.6 brings out the best performance, with an average accuracy of 85.27%, the precision of 91.41%, recall of 62.45%, and the F1-Score of 64.78%.