KRITERIA PENYAKIT TANAMAN KARET DENGAN METODE FORWARD CHAINING BERBASIS WEBSITE

Mulyadi, Dini Natia Utari
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Abstract

Like most plantation crops in general, rubber can be attacked by various diseases originating from fungi, pests, animals and even cancer cells. For that we need a method that is able to diagnose rubber disease. In previous studies related to plant disease diagnoses, among others, using the forward chaining method, certainty factor method and forward chaining. This study develops an analysis of the results of the diagnosis of rubber plant diseases using the expert system method. The choice of this method states that the Expert System method is capable of intuitively resembling the way the human brain works. With this method, it is hoped that the diagnosis of rubber plant diseases can assist farmers in detecting symptoms earlier so that the productivity of rubber plantations can be achieved. increase. The results of the research in the calculations carried out to diagnose rubber plant diseases, as many as 161 rubber plant object data are complemented by 33 identity symptoms and diagnoses from plantation data, then testing 60 rubber plant data without a diagnostic label, the accuracy value is obtained. of 81.28%. Likewise, testing by randomizing training data with Cross Validation obtained close results.
标准的前链胶原病基于网站
一般来说,像大多数种植园作物一样,橡胶会受到来自真菌、害虫、动物甚至癌细胞的各种疾病的侵袭。为此,我们需要一种能够诊断橡胶疾病的方法。在以往与植物病害诊断相关的研究中,主要采用正向链法、确定性因子法和正向链法。本文采用专家系统方法对橡胶植物病害诊断结果进行了分析。选择这种方法说明专家系统方法能够直观地类似于人类大脑的工作方式。通过这种方法,希望橡胶植物病害的诊断能够帮助农民早期发现症状,从而实现橡胶种植园的生产力。增加。研究结果在橡胶植物病害诊断的计算中,对多达161个橡胶植物对象数据进行了33个种植园数据的识别症状和诊断,然后对60个没有诊断标签的橡胶植物数据进行了测试,获得了准确度值。的81.28%。同样,通过交叉验证随机化训练数据的测试也得到了相近的结果。
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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