Sistem Pakar Diagnosis Penyakit Tanaman Padi Menggunakan Forward Chaining dan Dempster Shafer

Dianmita Ayu Putri, Arik Aranta
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引用次数: 3

Abstract

Rice (Oryza sativa) is one of the main commodities in Indonesia. One of the inhibitors of rice crop production is disease. Rice plant diseases can be caused by pathogens, host plants or bad environment. The process of diagnosing rice diseases requires expertise, knowledge and experience. This study aims to build an expert system that can diagnose 13 types of rice plant diseases from 43 symptoms based on the knowledge of 3 experts with forward chaining reasoning methods and mobile-based dempster shafer calculation methods. The testing technique used is black box testing, theoretical calculation testing, system accuracy testing and MOS (Mean Opinion Score) testing. The black box test results state that the expert system has 100% compatibility in terms of functionality. The theoretical calculation test results state that the expert system calculations are in accordance with the results of manual calculations. System accuracy testing results from 30 test cases get an accuracy of 81.11%. The results of MOS testing conducted on 30 respondents produced MOS of 4.2 from a scale of 5 categorized into a good system.
水稻(Oryza sativa)是印度尼西亚的主要商品之一。水稻产量的抑制因素之一是病害。水稻病害可由病原菌、寄主植物或恶劣环境引起。诊断水稻病害的过程需要专门知识、知识和经验。本研究旨在基于3位专家的知识,采用前向链推理方法和基于移动的dempster shafer计算方法,构建一个能够从43种症状中诊断13种水稻植物病害的专家系统。使用的测试技术有黑盒测试、理论计算测试、系统精度测试和MOS (Mean Opinion Score)测试。黑盒测试结果表明,专家系统在功能方面具有100%的兼容性。理论计算试验结果表明,专家系统计算结果与人工计算结果基本一致。30个测试用例的系统精度测试结果达到81.11%。对30名应答者进行的MOS测试结果显示,在5分的等级中,MOS为4.2分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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