Leaf Disease Detection Using Color Histogram and Random Forest on Pongamia Pinnata (L.) Pierre

Sarifah Agustiani, Agus Junaidi, Yoseph Arifin, Dwi Puji Hastuti, Sopiyan Dalis, Kartika Yuliantari, Fauzi Syarief

2023

Abstract

Increasing energy consumption, which is disproportionate to the energy supply, has resulted in an urge to seek renewable alternative energy sources that are environmentally friendly to meet energy needs. One plant with great potential to be used as an alternative fuel/biodiesel which environmentally friendly is Pongamia Pinnata (L.) Pierre. Besides many benefits and advantages of growing fast in tropical and sub-tropical areas, maintaining growth, and meeting the supply of bioenergy, it is necessary to have an intelligent system that can detect diseases in these plants. The research aims to classify Pongamia Pinnata into healthy and diseased categories. Hopefully, this system will prevent plant disease transmission and less-than-optimal growth. The method uses a color histogram as a feature extraction to recognize the characteristics of each image. In contrast, it uses a random forest algorithm for the classification process, and the accuracy reaches 99.79%.

Paper Citation

in Harvard Style

Agustiani S., Junaidi A., Arifin Y., Puji Hastuti D., Dalis S., Yuliantari K. and Syarief F. (2023). Leaf Disease Detection Using Color Histogram and Random Forest on Pongamia Pinnata (L.) Pierre. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 143-148. DOI: 10.5220/0012445100003848

in Bibtex Style

@conference{icaisd23,
author={Sarifah Agustiani and Agus Junaidi and Yoseph Arifin and Dwi Puji Hastuti and Sopiyan Dalis and Kartika Yuliantari and Fauzi Syarief},
title={Leaf Disease Detection Using Color Histogram and Random Forest on Pongamia Pinnata (L.) Pierre},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD},
year={2023},
pages={143-148},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012445100003848},
isbn={978-989-758-678-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD
TI - Leaf Disease Detection Using Color Histogram and Random Forest on Pongamia Pinnata (L.) Pierre
SN - 978-989-758-678-1
AU - Agustiani S.
AU - Junaidi A.
AU - Arifin Y.
AU - Puji Hastuti D.
AU - Dalis S.
AU - Yuliantari K.
AU - Syarief F.
PY - 2023
SP - 143
EP - 148
DO - 10.5220/0012445100003848
PB - SciTePress