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

Abstract

The democracy 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 by substantiating chi square in the selection of
dataset features. After testing 2809 data, the results of the
classification accuracy of support vector machine by 73.06%, and
support vector machine with chi square feature selection of
82.77% and F1-score 53.0764 against support vector machine and
F1-score 70.3222 support vector machine with chi square feature
selection.