Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Information System Exploration and Research
Ahmad, Burhan
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Ensemble Learning-based Potato Leaf Disease Classification Using DenseNet201 and MobileNetV2 Ahmad, Burhan; Alamsyah
Journal of Information System Exploration and Research Vol. 4 No. 1 (2026): January 2026
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v4i1.597

Abstract

Early and late blight are major threats to potato crops and can cause significant losses for farmers. Early disease classification is essential for quick and appropriate treatment. This study proposes an ensemble learning approach by combining DenseNet201 and MobileNetV2 architectures to classify potato leaf diseases from digital images. The dataset used consists of 2,152 potato leaf images and is processed through normalization, augmentation, and image resizing stages. The ensemble model was trained with optimized parameters and evaluated using accuracy, precision, recall, and F1-score. The test results showed an accuracy of 99.56%, with precision, recall, and F1- score values of 99.56% each. Demonstrated improved performance compared to single CNN models on the evaluated dataset, and offers an accurate and efficient solution for disease detection in the agricultural sector.
Co-Authors Alamsyah