SISTEM KLASIFIKASI JENIS KENDARAAN BERDASARKAN TEKSTUR MENGGUNAKAN ALGORITMA TRANSFORMASI HAAR WAVELET DAN MACHINE LEARNING

Nowadays, various vehicles have developed, which affects the different vehicle shapes. Therefore, the variety of vehicle types' traffic flow needs to be monitored by a classification system built in machine learning. This vehicle classification research uses four classes dataset of the vehicle, which is class 3 “Audi TL Acure Sedan 2012”, class 14 “Audi TTS Coupe 2012”, class 106 “Ford F-450 Super Duty Crew Cab”, and class 134 “Hyundai Sonata Hybrid 2012”. This research aims to evaluate the result of vehicle type classification using the transforms Haar wavelet algorithm as a feature extracted method. The result of the featured form transforms Haar wavelet algorithm decomposition levels 1 and 2, subsequently used as a training data model for classification on support vector machine and k-nearest neighbor. The highest classification result on training data model level 1 is in the Weighted KNN model with 0.33% and medium SVM with 0.33%. While decomposition level 2 is in the Weighted KNN model with 0.66%. At the same time, the training merge data model between levels 1 and 2 is in WeightedKNN with 0.75%.