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Fenry Winna Mutawally
Dept. of Mechanical and Biosystem Engineering IPB
Agriculture, Biological Sciences & Forestry

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Identifikasi Ganoderma Pada Tanaman Kelapa Sawit Berbasis Reflektansi Gelombang Multispektral Mohamad Solahudin Asyari; Fenry Winna Mutawally
Jurnal Keteknikan Pertanian Vol. 7 No. 3 (2019): JURNAL KETEKNIKAN PERTANIAN
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2603.129 KB) | DOI: 10.19028/jtep.07.3.193-200

Abstract

Basal Stem Rot (BSR) is a fatal disease caused by the fungus Ganoderma boninense. Currently in Indonesia the identification of oil palm plants suffering from BSR is done by directly observing oil palm plants one by one and pressing the palm tree trunks. However the direct checking method is felt to be less effective and efficient, its need another better method for detecting BSR. This study aims to evaluate the Ganoderma attack by using a multispectral camera, applying a neural network method to analyze NDVI images, and analyzing the effect of altitude on the accuracy of multispectral camera performance. In this study, spectral data of oil palm plants were taken through the air at an altitude of 50 m, 60 m, and 70 m with a multispectral camera mounted on a UAV, then the spectral data were analyzed using artificial neural networks to identify oil palm plants that were attacked by Ganoderma and healthy plants. The results of this study conclude that multispectral cameras can identify oil palm plants that have been attacked by Ganoderma at an altitude of 50 m and 60 m with utilization of artificial neural networks.
Co-Authors Mohamad Solahudin