Classification of Motorcyclists not Wear Helmet on Digital Image with Backpropagation Neural Network
Abstract: One of the world’s
leading causes of death is traffic accidents. Data from World Health Organization
(WHO) that there are 1.25 million people in the world die each year. Meanwhile,
based ondata obtained from Statistics Indonesia, traffic accidents from 2006 to
2013 continue to increase. Of allthese accidents, the largest accident occurred
at motorcyclists, especially motorcyclists who not wearing standard helmet. In
controlling the motorcyclists, police view directly at the highway, so that
there are weaknesses which there are still a possibility of motorcyclist
offenders who are undetectable especially for motorcyclists who are not wear
helmet. This paper explains research on image classification of human head
wearing a helmet and not wearing a helmet with backpropagation neural network
algorithm. The test results of this analysis is the application can performs
classification with 86.67% accuracy rate. This research can be developed into a
larger system and integrated that can be used to detect motorcyclists who are
not wearing helmet.
Author: Sutikno, Indra
Waspada, Nurdin Bahtiar, Priyo Sidik Sasongko
Journal Code: jptkomputergg160288
