Partner Sentiment Analysis for Telkom University on Twitter Social Media Using Decision Tree (CART) Algorithm

Abstract

Sentiment analysis is an analysis in terms of opinion and meaning in the form of writing. Sentiment analysis is very useful for expressing opinions from any individual or group to improve branding.  Branding is a process to promote and improve the name of a brand or brands to attract the attention of consumers to be interested in trying the services of a company that runs in academic terms such as Telkom University. However, this requires cooperation between other associations as partners so that the branding carried out can be effective. One form of cooperation is by providing opinions about Telkom University so that consumers are more familiar with Telkom University on Twitter social media which is the largest social media used by many people because it can provide any opinion freely. Therefore, this study aims to analyze the sentiment submitted by partners for Telkom University on Twitter which is the main factor for promoting themselves to consumers. The process carried out is to take all tweets about Telkom University submitted by partners and then carry out the TF-IDF weighting process and classified using the Decision Tree CART algorithm based on positive, negative, and neutral sentiment categories. The best results obtained by the Decision Tree model of the CART algorithm are the Accuracy value of 86.73%, Precision of 87.06%, Recall of 87.55%, and F1-Score of 86.52%.