Jatropha curcas disease identification using Fuzzy Neural Network

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Triando Hamonangan Saragih, Diny Melsye Nurul Fajri, Andi Hamdianah, Wayan Firdaus Mahmudy, Yusuf Priyo Anggodo

2017 Proceedings - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017 Vol. 2018-January Conference paper Cited by 4 Quartile

Abstract

Jatropha Curcas is a plant that has many functions and uses, but many part from that this plant can be attacked by disease. Expert systems can be applied in identification to help both farmers and workers to identify the disease. In this paper, the method used in the identification is Fuzzy Neural Network (FNN) that combine artificial neural networks with fuzzy logic techniques. A set of computational experiment reveal that the FNN obtains the best accuracy of 30%. © 2017 IEEE.

Affiliations

Faculty of Computer Science, Brawijaya University, Malang, Indonesia