Analisis Sentimen Opini Publik pada Channel Youtube Mata Najwa Menggunakan Metode SVM - Asmara Andhini; Fadilah Nuria Handayani; Intan Diasih; Nurmalitasari (Jurnal Teknik Informatika dan Teknologi Informasi, 2025)
The rapid development of social media, particularly the YouTube platform, has created an active and open space for public discourse. One prominent example is the program "Mata Najwa", which frequently discusses important societal issues. The episode titled "Retno Marsudi & Sri Mulyani: Women in Power Mata Najwa" garnered significant attention, sparking a variety of responses from netizens in the comments section. This study aims to explore public sentiment toward female leadership by utilizing the Support Vector Machine (SVM) classification method. A total of 4,626 comments from Najwa Shihab’s YouTube channel on the aforementioned episode were analyzed through several stages, including data preprocessing, sentiment labeling using a lexicon-based approach, feature extraction via the TF-IDF method, and classification using the SVM algorithm. The model evaluation demonstrated excellent performance, with an accuracy of 95.36%, precision of 95.70%, recall of 95.36%, and an F1-score of 95.27%. The model accurately identified positive and neutral comments but showed a limitation in detecting negative comments, likely due to class imbalance. This study offers new insights into public perceptions in digital spaces and reaffirms the effectiveness of SVM in text-based sentiment analysis.