Persepsi Publik Terhadap Perpindahan Ibu Kota Ke IKN Berdasarkan Analisis Sentimen X Menggunakan Naïve Bayes Classifier - Fauzan; Wiwik Kusrini; Fathurrahmani (POSITIF : Jurnal Sistem dan Teknologi Informasi, 2025)
The relocation of Indonesia’s capital city from Jakarta to Nusantara (IKN) has become a topic that generates various public reactions. These opinions are largely expressed through the social media platform X (formerly Twitter), making it an important data source for analyzing public sentiment. This study aims to apply the Naïve Bayes Classifier method to analyze public sentiment toward the relocation of IKN and to evaluate its accuracy using a Confusion Matrix. The data were collected through a web crawling process on the X platform using the keyword "ikn", resulting in 1,002 relevant tweets. The data were then processed through preprocessing stages using Python, including lowercasing, punctuation removal, tokenizing, stopword removal, stemming, and TF-IDF value calculation to form features. After augmentation, the number of data increased to 1,324, which was divided into 75% training data and 25% testing data. Sentiment classification was performed using the Naïve Bayes Classifier algorithm, and testing was conducted using the black-box method to ensure system functionality according to the design. Model performance evaluation using a Confusion Matrix produced an accuracy of 92.47%, precision of 93.03%, recall of 92.47%, and F1-score of 92.45%. The web-based system developed in this study is expected to help the government understand public opinion and develop more effective communication strategies related to the IKN relocation policy.