Skripsi

DETEKSI PELANGGARAN DAN KECEPATAN KENDARAAN MENGGUNAKAN YOLO DAN ALGORITMA DEEPSORT PADA REKAMAN VIDEO DI JALAN PROTOKOL DI KOTA PALEMBANG

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The purpose of this research is to create a detection system for violations of not using helmets and speed limit violations at several road points in Palembang City. This research uses YOLOv8 combined with Deepsort to detect the number of vehicles, especially the class of motorcycles not using helmets and speed detection. As a result, the accuracy of detection of violations not using helmets reached 89.69% and for speed violations had a MAPE (Mean Absolute Percentage Error) value of 12%. The category of violation level is predicted using KNN by dividing low, medium, and high violation levels. The results of category prediction using KNN have an accuracy rate of 89.6% by comparing the prediction results and manual calculations.

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Detail Information

Series Title

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Call Number

T1520562024

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xv, 130 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.370 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

-

Subject(s)

Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

KA

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