GDL

Nitrogen (N) is one of the most important nutrients for the growth of rice crops. Unbalanced and excessive use of N-fertilizers causes environmental pollution, reduces quality of the crop, and increases pest pressure, in addition to the increasing cost to farmers from excessively applied fertilizers and pesticides. The goal of this paper is to build mobile applications which can analyze and recommend nitrogen elemental requirements in rice plants based on the color of rice leaves. This application has embedded a set of stages of the process for image processing and classification which is used to analyze the color of rice leaves captured through a smartphone camera. Image processing in this application is a feature extraction of red, green, and blue (RGB) values to obtain a characteristic on the leaf color image. Then the result of feature extraction is used to classify the color level of rice leaf by using a K-Nearest Neighbor method. The results of accuracy test show that accuracy of the application in analyzing and recommending nitrogen fertilizer needed by rice crops, on average, is 66.67%.

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