Analisis Respon Publik Terhadap Tren Penggabungan Foto Gemini AI Menggunakan Naive Bayes - Afiani, Nanda; Mahenra, Ridwan (Forum Kerjasama Pendidikan Tinggi, 2025)
The rapid advancement of Artificial Intelligence (AI) technology has brought numerous innovations to the digital world, one of which is Gemini AI — an application capable of automatically merging photos based on user instructions. This phenomenon has gone viral on the TikTok platform and has sparked diverse public reactions, ranging from admiration for its visual results to concerns about ethical issues and the potential misuse of deepfake technology. This study aims to analyze public sentiment toward the trend of Gemini AI photo merging on TikTok using a sentiment analysis method based on the Naïve Bayes algorithm. Data were collected through a web scraping technique using the Apify platform, resulting in 5,061 user comments. The data processing stages included text preprocessing, TF-IDF transformation, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that neutral sentiment dominates (4,059 comments), followed by positive (745 comments) and negative (257 comments). The dominance of neutral sentiment occurs because most user comments are informative or descriptive, expressing ordinary responses without strong emotional tones, rather than showing indifference to ethical concerns. The Naïve Bayes model demonstrated good performance with an accuracy of 85.72%, precision of 87.84%, recall of 85.72%, and F1-score of 81.95% through 5-fold cross-validation. These findings confirm that the Naïve Bayes algorithm is effective for classifying public opinion toward generative AI technologies. Overall, this study contributes to a deeper understanding of public perception of AI innovations in the creative digital domain and their social implications on social media platforms.