This study aims to analyze traffic density in Palembang City by utilizing YOLOv9 for vehicle detection from CCTV recordings and employing K-Nearest Neighbors (KNN) and Long Short-Term Memory (LSTM) to assess density based on the detected vehicle count. The results indicate that YOLOv9 with 100 epochs achieved the best performance, with a mean Average Precision (mAP) of 0.844 for training, 0.843…