Analisa Sentimen Rencana Pemindahan Ibu Kota Nusantara dari Jakarta ke Kalimantan Timur Menggunakan Algoritma Naïve Bayes - Azis, Iim Muhaemin Abdul; Wahyudi, Tri (Jurnal Indonesia : Manajemen Informatika dan Komunikasi, 2024)
The relocation of Indonesia's capital city has been a highly debated topic in recent years. This decision has sparked various opinions and views from the public, especially as reflected on social media platforms like Twitter. This research aims to understand the perspectives and attitudes of Indonesian citizens regarding the plan to move the capital to Nusantara, as expressed on Twitter. Sentiment analysis using the Naïve Bayes algorithm is employed to classify tweets into positive and negative sentiment categories. By leveraging data from Twitter, this study aims to provide deeper insights into public perception and attitudes towards the relocation of the government center. The research used a dataset of 375 tweets. The results, analyzed using RapidMiner, show that the precision for positive sentiment is 94.89% and for negative sentiment is 65.00%. The recall for negative sentiment is 48.15%, while the recall for positive sentiment reaches 97.38%. The model's accuracy is 92.82%, indicating that the Naïve Bayes algorithm can effectively classify sentiments using the available data. This study offers insights into public support and opposition, as well as the factors influencing their attitudes towards the capital relocation plan.