Sentiment Analysis For The 2024 Presidential Election (Pilpres) Using BERT CNN - Daffa Fadhilah Putra; Yuliant Sibaroni (Eduvest - Journal of Universal Studies, 2024)
The 2024 presidential election in Indonesia has generated tremendous enthusiasm on social media, particularly on the X platform. This research aims to analyze public sentiment regarding the 2024 presidential election by utilizing BERT and CNN methods. Sentiment analysis in the digital era is key to understanding the diverse social perspectives within society. The use of BERT, which has proven effective in understanding natural language context, and CNN, initially used for image analysis, will help in understanding public sentiment on X leading up to the 2024 presidential election. The research results show that the BERT model provides the best performance with an average accuracy of 90.02%, while CNN achieved 88.19%. The sentiment-based predictions using BERT for the three presidential candidates indicate that Prabowo Subianto is predicted to receive the highest support at 43.82%, followed by Ganjar Pranowo with 33.83%, and Anies Baswedan with 22.35%. A comparison of the prediction results with the actual election results shows that Prabowo Subianto was predicted to receive 43.82% of the vote, while the actual election results reached 58.58%, a difference of 14.76%. Ganjar Pranowo was predicted to receive 33.83% of the vote, while the actual results were 16.47%, with a difference of 17.36%. Anies Baswedan was predicted to receive 22.35% of the vote, with the actual result being 24.95%, a difference of 2.60%. This study indicates that the BERT model is effective in providing an accurate depiction of the 2024 Indonesian presidential election results.