KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)
Vol 11, No 1 (2024)

Sistem Rekognisi Jenis Kendaraan Dengan Analisis Video Menggunakan Metode Yolov4

Dharma, Ichsan Surya (Unknown)



Article Info

Publish Date
28 Feb 2024

Abstract

Traffic density on the highway, especially at intersections where there are traffic lights, is a number that can be used to estimate the number of vehicles. The increase in the density of highways is directly proportional to the growth in Indonesia's population which is increasing. The problem was found that the survey to record the types of vehicles in Indonesia was still manual by taking notes and coming directly to the location. Based on this problem, a vehicle object detection system was created, especially cars based on their brands and variants to facilitate the police survey process to detect violations that have occurred. This study uses the You Only Look Once (YOLOv4) algorithm to detect cars, and classify and determine the level of accuracy. This research uses 7034 image dataset with 8 classes, namely Motorcycle, Suzuki Ertiga, Honda Jazz, Honda Brio, Toyota Avanza, Toyota Innova, Mitsubishi Xpander, Mitsubishi Pajero Sport. The results of this study indicate that the YOLOv4 algorithm can be used on Jogja CCTV to detect vehicle types with an accuracy of 82%.

Copyrights © 2024






Journal Info

Abbrev

klik

Publisher

Subject

Computer Science & IT

Description

KLIK Scientific Journal, is a computer science journal as source of information in the form of research, the study of literature, ideas, theories and applications in the field of critical analysis study Computer Science, Data Science, Artificial Intelligence, and Computer Network, published two ...