KLASIFIKASI KENDARAAN BERMOTOR DENGAN MULTI KERNEL SUPPORT VECTOR MACHINE

Abstract

Since October 2017, Electronic automatic payments have been applied in all Indonesian toll roads. This payment system needes an extra system which is able to distinguish the types of motor vehicles that will enter the toll road due to the regulation itself which allow four-wheel or more vehicle to pass the toll road. This automatic system can be built by a classification algorithm, and one of the best is Support Vector Machine (SVM), in order to be able to classify non-linear separable data, SVM must be modified by giving kernel function on it. Furthermore, determining the approriate kernel for every classification problem is a fundamental step, and that’s obviously not easy, to solve that problem the researchers found a method that can make this kernel function more flexible, this method called Multi Kernel Learning (MKL). Main idea of this method is formulating some kernel function to be one kernel function. This framework is built an automatic system to classify the types of motor vehicles using Support Vector Machine modified using Multi Kernel Learning method. The experimental result shows that the system has a good average value of accuracy that is 84.60%, the average value of precision is 84.95% and also average value of recall is 84.60%.
 Keyword: Kendaraan Bermotor, Klasifikasi, Multi Kernel, Support Vector Machine