Disease Detection System in Rice Plant Based on Artificial Intelligence

Abstract

Indonesia is an agricultural country with the majority of the population working as farmers and owning agricultural land of 13% of the country's total area. The main commodity of Indonesian agriculture is rice, because this plant is a food crop that produces rice as the staple food of the community. Based on the data collected, it is noted that there are frequent fluctuations in the total rice harvest each year. This is caused by various factors, ranging from the lack of agricultural land compared to population growth, conversion of agricultural land to non-agricultural land, to the biggest problem, namely pests and diseases that attack rice plants. Disease problems in rice plants have caused many cases of crop failure that have occurred in all parts of Indonesia. With the development of technology, this research developed a system for detecting rice plant diseases based on artificial intelligence and an expert system. Farmers simply use their gadgets to diagnose diseases independently without having to involve experts directly, but of course with the same optimal results as expert diagnoses. The method used is the ESDLC (Expert System Development Life Cycle) method which consists of assessment, expert knowledge mapping, design and testing. The results obtained in this study are the existence of an application for detecting rice plant diseases based on artificial intelligence using an expert system method that can be used by farmers to diagnose rice plant diseases independently without having to meet directly with experts

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