TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 14, No 3: September 2016

Classification of Motorcyclists not Wear Helmet on Digital Image with Backpropagation Neural Network

Sutikno Sutikno (Diponegoro University)
Indra Waspada (Diponegoro University)
Nurdin Bahtiar (Diponegoro University)
Priyo Sidik Sasongko (Diponegoro University)



Article Info

Publish Date
01 Sep 2016

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 on data obtained from Statistics Indonesia, traffic accidents from 2006 to 2013 continue to increase. Of all these 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.

Copyrights © 2016






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...