Article Per Year (5 Year)
p-Index From 2021 - 2026
1.8
P-Index
This Author published in this journals
All Journal Jurnal TIMES Jurnal SOLMA Jurnal Fisika : Fisika Sains dan Aplikasinya Jurnal Teknik Informatika (JUTIF) Journal of Energy, Material, and Instrumentation Technology Wiga : Jurnal Penelitian Ilmu Ekonomi Aptekmas : Jurnal Pengabdian Kepada Masyarakat Socius: Social Sciences Research Journal Journal of Language Intelligence and Culture Saturnus: Jurnal Teknologi dan Sistem Informasi
Firdaus, Iqbal
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Classification of Banana Leaf and Ornamental Plant Diseases Using Gray Level Co-occurrence Matrix (GLCM) and Hybrid Random Forest–Support Vector Machine (SVM) Urfiyati, Novia; Rijati, Nova; Pujiono, Pujiono; Soeleman, Arief; Firdaus, Iqbal; Nurhuda, Yeni Agus
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.4966

Abstract

Leaf diseases in banana plants and ornamental crops can significantly reduce productivity and product quality, highlighting the need for accurate early detection methods. This study proposes an image-based classification approach utilizing texture features extracted from the Gray Level Co-occurrence Matrix (GLCM) combined with a Hybrid Stacking model that integrates Random Forest (RF) and Support Vector Machine (SVM). The preprocessing stage involves image resizing and noise reduction, followed by feature extraction using energy, contrast, homogeneity, and correlation parameters. The dataset consists of eight classes of healthy and diseased leaves, collected from both field documentation and secondary sources. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics under a cross-validation scheme. Experimental results show that SVM achieved 89.2% accuracy, RF 88.5%, while the stacking model yielded the best performance with 91.7% accuracy, effectively reducing misclassification among visually similar disease classes. This study demonstrates the effectiveness of combining GLCM features and hybrid stacking models for leaf disease classification, with potential applications in automated plant monitoring systems to support precision agriculture.
Co-Authors Abdul Kadir Abdurrahman, Ahmad Faruq Agung Putra Wijaya Boedi, Soelistijono Budi Dermawan Diba Ramadhana Dwi Asmi Eliasta Ketaren, Eliasta Firdaus, Gusti Aditya Aromatica Henny Septiana Amalia Jacob, Louris Maisarah, Hj. Melya Riniarti Muhammad Maladi Nova Rijati Nurhuda, Yeni Agus Pohan, Sry Dhina Posman Manurung Pujiono Pujiono Raffa, Muhammad Rio, Avilla Riswan Ludfi Siska Ayu Widiana Soeleman, Arief Soeleman, M. Arief Sumardi . Supriyanto Urfiyati, Novia Wijaya, Mario Eka Zaharani, Rethanita