Penerapan Algoritma Support Vector Machine Pada Analisis Sentimen Hashtag Twitter

Abstract

The development of the creative industry in Indonesia is marked by the emergence of content creators such as YouTubers and celebrities. With the emergence of content creators, people in these professions must be more creative and come up with new things in accordance with community trends in accordance with applicable laws in Indonesia. Twitter is one of the social media that can be used to share online and provide information in accordance with the prevailing trends in society. Hashtags or hashtags on Twitter are often used by users to add comments so that when the hashtag is used a lot it will become a trending topic. By analyzing sentiment on trending topics, positive and negative tendencies will be obtained that can help the content creator profession to create content. This study uses the Support Vector Machine (SVM) method to conduct a sentiment analysis process about the twitter hashtag. The data used is hashtag data on twitter. The data that has been obtained is then carried out by text preprocessing, then weighting, and finally sentiment analysis using SVM. This study uses tweet data taken on October 29, 2022 as many as 21 data, namely “BeliPulsaDiGrab” which has two sentiment classes, namely positive sentiment as much as 99% and negative 1% data