KLASIFIKASI JENIS RETAKAN PADA BETON MENGGUNAKAN ALGORITMA HISTOGRAM OF GRADIENTS DAN MACHINE LEARNING

Concrete crack frequently is a serious problem occurs around building structure and road structure. There are requirements to be an early inspection before the concrete used. This research builds a model to classify type concrete surface by Image Processing. In this era, technology always continues to develop a Machine Learning is Artificial Intelligence to help human’s work from any sector such as medical, economic, agriculture and other. Concrete structure inspection can be worked by builds Machine Learning system within concrete crack surface image as input data. The model system in this research using HOG feature extraction and SVM-KNN classification. The HOG extraction feature process using 50 60 cell size then it worked as shape feature and object detection as numerical extraction. Accuracy training and performance matrix on testing will be set as parameter model. The result shows model on HOG 1 using Medium Guassian SVM the training accuracy 89%, HOG 2 using Quadratic SVM the training accuracy 82.40% and HOG 3 using Quadratic SVM the training accuracy 90.20%.