Implementasi Algoritma YOLO Dalam Pengklasifikasian Objek Transportasi pada Lalu Lintas Kota Medan

Muhammad Agus Syaputra
Josua Pinem
Afiq Alghazali Lubis
Yuva Denia

Populer: Jurnal Penelitian Mahasiswa
Vol. 3 No. 1 (2024): Maret : Jurnal Penelitian Mahasiswa

This research allows an automated system for detecting classified means of transportation in Medan City traffic using the YOLOv8 algorithm. The YOLOv8 algorithm is used to detect transportation objects with accuracy that is many times better than other object detection algorithms and with good accuracy after training with various data sets. The use of this algorithm provides an effective solution for handling congestion in the form of increasing the number of vehicles and less orderly traffic users in the city of Medan. The placement of each transportation object in the image to be tested by the system has an influence on the shape accuracy of the object detection results by the algorithm.