Sentiment Analysis of DKI Jakarta 2024 Election (Case Study: Anies Baswedan and Ridwan Kamil) - Muhammad Safrul Safrudin; Syarifah Aini (Universitas Atma Jaya Yogyakarta, 2024)
This study analyzes public sentiment toward two potential candidates for the 2024 Jakarta gubernatorial election, Anies Baswedan and Ridwan Kamil, using Twitter data. Applying the TextBlob model for text extraction and Naive Bayes for sentiment classification found that sentiment toward Anies Baswedan is mostly positive, 52.2%, while neutral sentiment dominates for Ridwan Kamil. The accuracy of the Naive Bayes model reached 80% for Anies Baswedan and 72% for Ridwan Kamil, with higher precision, recall, and F1-score for Anies' data. These results indicate that the model is more accurate in classifying sentiment toward Anies compared to Ridwan Kamil. The implications of these findings are important for political campaign strategies, where Anies can leverage the existing positive support, while Ridwan Kamil has an opportunity to strengthen public engagement through a more strategic approach, in line with the sentiment emerging on social media.