# ESforRPD2: Expert System for Rice Plant Disease Diagnosis

## TL;DR

This paper introduces an expert system to help Indonesian farmers diagnose rice plant diseases early using expert knowledge and surveys.

## Contribution

The novel contribution is the development of ESforRPD2, an expert system for rice plant disease diagnosis with 87.5% accuracy.

## Key findings

- ESforRPD2 detects 48 symptoms and 8 rice plant diseases with 87.5% accuracy.
- The system was developed using expert knowledge from East Kalimantan rice experts.
- The system is designed to assist farmers in early disease diagnosis.

## Abstract

One of the factors causing rice production disturbance in Indonesia is the lack of knowledge of farmers on early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make early diagnosis of rice plant diseases.

Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts, and uses a Waterfall Paradigm and Unified Modelling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with an accuracy of 87.5%.

ESforRPD2 is available in Indonesian at:
http://esforrpd2.blog.unmul.ac.id