Classification of Rice Leaf Diseases Based on Texture and Leaf Colour

Abstract

Agriculture is a sector that contributes greatly to the Indonesian economy. The role of the agricultural sector in economic development in Indonesia is as a producer of food. The high demand for rice as a staple food in the community requires farmers to be able to produce rice of good quality and in large quantities to meet the needs of the community. One of the factors that affect the quality of rice plants is the attack of pests and diseases. Farmers have difficulty in identifying pests and diseases in rice plants due to limited knowledge. Improper handling of rice plants that are attacked by pests and diseases will result in decreased yields and farmers suffer losses. The problems that occur require a solution so that by designing a modeling of identification of pests and diseases it can be fast and accurate based on the texture and color of the leaves. Disease identification consisted of brown spot and leaf blight using rice leaf imagery using GLCM and K-NN. The results of the application of GLCM feature extraction and classification using the K-NN method are very good with an accuracy rate of 89%.