ANALISIS SENTIMEN TERHADAP MINAT MASYARAKAT JAKARTA YANG MEMILIH KENDARAAN UMUM MENGGUNAKAN ALGORITMA NAÏVE BAYES - Yogga Tolly Dewanto; Ade Davy Wiranata; Mia Kamayani Sulaeman (ISTEK WIDURI, 2025)
The worsening traffic congestion in Jakarta highlights the need to understand public interest in using public transportation. Social media platforms such as X serve as valuable sources of real-time public opinion data. This study aims to analyze the sentiments of Jakarta residents toward public transportation to identify the factors influencing their interest in using it. Data was collected from X and analyzed using the Naïve Bayes algorithm through the RapidMiner application. The analysis was conducted by splitting the dataset into 60% training data and 40% testing data. The results of the study show 203 positive sentiment data, 135 negative sentiment data, and 138 neutral sentiment data. Positive sentiments were mostly associated with affordability and ease of access, while negative sentiments were related to discomfort and lack of punctuality. This research is expected to serve as a reference for policymakers in improving the quality of public transportation services in Jakarta.