Analisis Sentimen Terhadap Kontroversi Pembangunan IKN Di Media Sosial Twitter Menggunakan Metode Naive Bayes

Abstract

The relocation of Indonesia's capital city (IKN) from Jakarta to East Kalimantan is a national strategic policy that has generated diverse public responses. On one hand, it is seen as an effort to promote equitable development, but on the other hand, it has drawn criticism related to its environmental, social, and financial impacts. Social media, particularly Twitter, has become a popular platform for expressing public opinion on this issue. This study aims to analyze public sentiment toward the IKN development as expressed through Twitter posts. By understanding public sentiment trends, this research seeks to provide insights into public perception that may serve as valuable input for government evaluation and policymaking. The research employed a quantitative approach using data mining techniques. Data were collected through web crawling using the snscrape library and underwent several pre-processing stages, including cleansing, case folding, tokenization, stopword removal, and stemming. Sentiment analysis was conducted using a lexicon-based approach, combined with a Naïve Bayes classification algorithm supported by TF-IDF weighting. Based on 2,178 analyzed tweets, the results showed that positive sentiment dominated at 52.4%, followed by negative sentiment at 28.4%, and neutral sentiment at 19.3%. The classification model achieved an accuracy rate of 75.69%. These findings indicate a general tendency of public support for the IKN development and highlight the importance of sentiment analysis as a strategic tool for interpreting public opinion in the digital era