Implementing Backward Chaining Method in Expert System to Detect and Treat Rice, Chilli, and Corn Plant's Pests and Diseases release_bwimqndt65dslaivsmwfti756a

by Primaadi Airlangga, Anton Muhibuddin, M. Mirza Sulthoni, Aries Budi Wicaksana

Published in Journal on Information Technology and Computer Engineering by Perpustakaan Universitas Andalas.

2018   Issue 02, p21-25


Indonesia is an agrarian country which most of it's citizens are farmer. There are various kind of decent plants to grow in Indonesia but most of them plant rice, corn, wheat, and sago as staple food. There other plants that is consumed not as main food but as subsidiaries, one of them are chilli pepper. Abundant variety of vegetation in Indonesia means that there are also many type of pests and diseases. An agriculture expert is needed to identify plant's diseases and pest correctly. Meanwhile, the number of agriculture experts is insufficient to help massive amount of farmer whom have trouble in agriculture. This problem can be solved by using Expert System where farmers can detect the problem on their plants and finding treatment to cure their plants correctly them self. This research is mean to develop an Expert System Application in agriculture  to identify diseases and pests based on their symptoms especially rice, chilli, and corn plants. This Expert System is based on web program using Backward Chaining Inversion which is deemed necessary to solve the case study's problem.  Responsive Web Based System can be  accessed by user or client from many devices especially their smart phoneto hel diagnose disease that occurs to their plant, more over, to solve the low rate of expert on agriculture.
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