Journal ID : TRKU-08-07-2020-10869
[This article belongs to Volume - 62, Issue - 06]
Total View : 290

Title : A Detection System of Pests and Diseases For Corn Plant Using Certainty Factor and Fuzzy Sugeno Methods

Abstract :

Corn is one of the leading food that produces carbohydrates in Indonesia. It can grow well in hot and cold areas with sufficient rainfall and irrigation. However, each part of the corn is sensitive to several diseases, and it can reduce the quantity and quality of the corn result production. Damage of corn plant that is caused by the disease can be conducted by the disturbing process into the plant and make the plant died. The diseases can undermine corn plants by disrupting the processes inside the plant and make the plant died. Therefore, this study aims to design a system for detecting diseases and pests in corn plants using Certainty Factor and Fuzzy Sugeno methods. The Fuzzy Sugeno method is employed to identify diseases and pests in corn plants based on the degree of trust in the diseases of the corn plants. The degree of confidence in the disease can be obtained from the certainty level of the base system built by the Certainty Factor method. The experiments have been carried out to determine the accuracy of the Certainty Factor and Fuzzy Sugeno methods. Therefore, the detection system can work effectively and efficiently as well as minimize the amount of damaged corn production. We collected 15 diseases or pests and 48 symptoms, and the experiment results have obtained an accuracy of 85.16%

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