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All Journal Jurnal Fitopatologi Indonesia Jurnal Penelitian Tanaman Industri Buletin Tanaman Tembakau, Serat & Minyak Industri Journal of Information Technology and Computer Science Buletin Tanaman Tembakau, Serat & Minyak Industri Perspektif, Review Penelitian Tanaman Industri
Titiek YULIANTI
Balai Penelitian Tanaman Pemanis dan Serat
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Medicine & Pharmacology

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Journal : Journal of Information Technology and Computer Science

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Detection of Disease and Pest of Kenaf Plant using Convolutional Neural Network Fajri, Diny Melsye Nurul; Mahmudy, Wayan Firdaus; Yulianti, Titiek
Journal of Information Technology and Computer Science Vol. 6 No. 1: April 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1026.462 KB) | DOI: 10.25126/jitecs.202161195

Abstract

Kenaf fiber is mainly used for forest wood substitute industrial products. Thus, the kenaf fiber can be promoted as the main composition of environmentally friendly goods. Unfortunately, there are several Kenaf gardens that have been stricken with the disease-causing a lack of yield. By utilizing advances in technology, it was felt to be able to help kenaf farmers quickly and accurately detect which pests or diseases attacked their crops. This paper will discuss the application of the machine learning method which is a Convolutional Neural Network (CNN) that can provide results for inputting leaf images into the results of temporary diagnoses. The data used are 838 image data for 4 classes. The average results prove that with CNN an accuracy value of 73% can be achieved for the detection of diseases and plant pests in Kenaf plants.
Co-Authors . Supriyono, . A.A. Ketut Agung Cahyawan W Cece SUHARA Fajri, Diny Melsye Nurul Hargiani, Fransisca Xaveria Heri Prabowo IGAA. INDRAYANI, IGAA. Rizqiyah, Sakinah Inayatur SRI HENDRASTUTI HIDAYAT Wayan Firdaus Mahmudy