Support Vector Machine With Feature Selection Chi-Square On Analysis Twitter Sentiment

Abstract

The Democratic party that occurred in Indonesia caused an increase in public comments on social media. Twitter is one of the most famous social media platforms in Indonesia. By utilizing a dataset of various public comments on the 2024 general election, we can do sentiment analysis. Sentiment analysis is carried out for the purpose of extracting positive or negative patterns of people's behavior in the implementation of the 2024 election. The algorithm used in analyzing sentiment is a support vector machine that substantiates chi-square in the selection of dataset features. After testing 2809 data, the results of the classification accuracy of the support vector machine was 73.06%, and the support vector machine with chi-square feature selection of 82.77% and F1-score 53.0764 against the support vector machine and F1-score 70.3222 support vector machine with chi-square feature selection.