Identification leaf disease on anthurium and rice using wavelet with K-nearest neighbors

Abstract

Leaf disease on Anthurium and rice can inflict financial loss to farmers. Eradication of the diseases can done, determining the type of disease is still difficult. This research proposed a new study on measuring for automatically identification of plant disease based on leaf image with the input of digital image. Detection process started with feature extraction using Haar wavelet transform and the identification process using the k-Nearest Neighbor (k-NN). This study, used the image which consists of seven hundred images, divided into seven classes consisting of 80% for training data and 20% for test data. The experimental result showed that identification of plant disease with leaf anthurium using k-NN is better than that of leaf anthurium and rice. The experimental result show that the accuracy system is 72.8%.