Analisis Sentimen Terhadap Calon Presiden Indonesia 2024 dengan Metode Extreme Gradient Boosting (XGBOOST)
This research takes Twitter data to see public opinion on presidential candidates, and determines the process of digital text analysis and the application of the XGBOOST method to Twitter user sentiment in two categories (positive and negative) and three categories (positive, negative and neutral) for each candidate.
Abstract
In 2024, Indonesia will implement democracy in the election of the Indonesian head of state. Any political figure who runs for head of state and calculates his popularity based on public opinion. After the General Election Commission (KPU) released the names of the 2024 Indonesian presidential candidates, these names were widely discussed, especially on social networks, one of which was Twitter. Twitter or what is often called X is a platform that provides short, concise and clear information. Twitter users responding to the 2024 presidential candidate have different opinions on Twitter. The sentiments used are positive, negative and neutral. The method used to analyze public opinion with data processed on Twitter social media uses Extreme Gradient Boosting (XGBOOST), classifying tweet test data in the form of classification with prediction output with accurate values. This research takes Twitter data to see public opinion on presidential candidates. The aim of this research is to determine the process of digital text analysis and the application of the XGBOOST method to Twitter user sentiment in two categories (positive and negative) and three categories (positive, negative and neutral) for each candidate, namely Ganjar Pranowo, Anies Baswedan and Prabowo Subianto. The results show an accuracy of 0.96%, precision of 0.96% and recall of 0.97%.