Expert System on Soybean Disease Using Knowledge Representation Method

Abstract

Soybean (Glycine mx L.) is one of the important strategic commodity in Indonesia which is cultivated widely. Soybean demand continues rise increasly demand for soy as food industry ingredients such as tofu, tempeh, soy milk soy tauco and snack. However, efforts to increase the production and development of soybean agribusiness has some constraints that may reduce production by 50% due to certain diseases. The situation is of course very detrimental to soybeans in particular and the public in general. But the farmers have very low knowledge about the technical maintenance of the soybean crop. These circumstances resulted in a high dependence of farmers on crop pest controllers are limited. To overcome these problems was made based application based mobile operating system Android. However, mobile devices have limitations in computing resources ranging from the ability of the processor to the memory capacity. To optimize computing resources on mobile devices, we need a method of knowledge representation that consists of a frame-based and rule-based representation with the rules or rule that is used to determine whether the peanut plants infected with certain diseases, in which the types of diseases that can be detected on do this thesis includes diseases of bacterial pustules, antarchnose disease, mosaic virus disease, damping, rust disease and blight. then analyzed knowledge representation which is the most optimal. This can be done by comparing the scenario some knowledge of the representation of the level of validity and cases symptoms can be resolved.

Keywords: expert system,soybean disease ,android,knowledge representation