Optimalisasi Identifikasi Sidik Jari Menggunakan Metode Neural Network Pada Keamanan Sepeda Motor

Abstract

Motorcycle theft rate each year is quite high. The cause of the rampant motorcycle theft due to the weakness of the security system on the motorcycle. Therefore required a system that can overcome the breaking of a motorcycle. One of them by making a security system on a motorcycle. A growing security system is using fingerprints. Fingerprints or human fingerprints have different characteristics in each individual. To be able to use fingerprint as authentication tool used Fingerprint Scanner Sensor. But sometimes there are still errors that occur in the recognition process caused by the problem of less accurate sensor specifications. Therefore, the authors do research by making a motor security system using fingerprints that are integrated with Neural Network alghoritma. The Neural Network algorithm is used to optimize the fingerprint recognition process, thereby reducing the error in the identification process. The result of this research is to produce motorcycle equality system using fingerprint integrated with Algorithm Neural Network, so that motorcycle can only be turned on by motor owner.