Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Vol 7, No 1 (2021): April

Jatropha Curcas Disease Identification using Random Forest

Triando Hamonangan Saragih (Lambung Mangkurat University)
Vivi Nur Wijayaningrum (Politeknik Negeri Malang)
Muhammad Haekal (Lambung Mangkurat University)



Article Info

Publish Date
13 Apr 2021

Abstract

As one of the most versatile plants, Jatropha curcas is spread in various regions around the world because of the great benefits it provides. However, Jatropha curcas is easily attacked by viruses which then cause damage to the plant, such as yellowing leaves and secreting sap, making it necessary to identify Jatropha curcas disease to deal with the problem as early as possible so that the losses incurred are not too large. An expert system was built to be able to identify Jatropha curcas disease by adopting expert knowledge. The use of the Random Forest algorithm as one of the classification algorithms was applied in this study. By using a random forest, several disease prediction classes are generated by each decision tree that has been formed. The disease class with the most votes was used as the final result. In this study, the data used were 166 data with 9 diseases and 30 symptoms. The results showed that Random Forest outperformed other algorithms such as Fuzzy Neural Network and Extreme Learning Machine with an accuracy of 98.002% using the composition of training data and test data of 70:30.

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Journal Info

Abbrev

JITEKI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical ...