Jatropha curcas disease identification with extreme learning machine

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Triando Hamonangan Saragih, Diny Melsye Nurul Fajri, Wayan Firdaus Mahmudy, Abdul Latief Abadi, Yusuf Priyo Anggodo

2018 Indonesian Journal of Electrical Engineering and Computer Science Vol. 12 Issue 2 Article Cited by 5 Quartile

Abstract

Jatropha is a plant that has many functions, but this plant can be attacked by various diseases. Expert systems can be applied in identifying so that can help both farmers and extension workers to identify the disease. one of method that can be used is Extreme Learning Machine. Extreme Learning Machine is a method of learning in Neural Network which has a one-time iteration concept in each process. In this study get a maximum accuracy of 66.67% with an average accuracy of 60.61%. This proves the identification using Extreme Learning Machine is better than the comparison method that has been done before. © 2018 Institute of Advanced Engineering and Science.

Affiliations

Faculty of Computer Science, Brawijaya University, Malang, 65145, Indonesia; Faculty of Agiculture, Brawijaya University, Malang, 65145, Indonesia; Data Analyst, Ilmuone Data, Jakarta, 12190, Indonesia