KLASIFIKASI CITRA DENGAN POHON KEPUTUSAN - Kusrini Kusrini; Sri Hartati; Retantyo Wardoyo; Agus Harjoko (Department of Informatics, Institut Teknologi Sepuluh Nopember, 2008)
Image classification can be done by using attribute of text that come along with the image, such as file name, size, or creator. Image classification also can be done base on visual content of the image. In this research, we implement a image classification model base on image visual content. The image classification is based on decision tree method that adapt C4.5 algorithm. The decision variable used in the decision tree generation process is image visual features, i.e. color moment order-1, color moment order-2, color moment order-3, entropy, energy, contrast, and homogeneity. The result of this research is an application that can classified image base on the knowledge of the previous classification cases. Keywords: image classification, decision tree, C4.5 algorithm