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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Vokasi Jurnal Sains dan Teknologi Jurnal Sarjana Teknik Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Jurnal Pengabdian UntukMu NegeRI Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING ILKOM Jurnal Ilmiah Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat Martabe : Jurnal Pengabdian Kepada Masyarakat JURTEKSI Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jambura Journal of Informatics Building of Informatics, Technology and Science JISKa (Jurnal Informatika Sunan Kalijaga) Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Informatika dan Rekayasa Perangkat Lunak International Journal of Advances in Data and Information Systems Jurnal REKSA: Rekayasa Keuangan, Syariah dan Audit Innovation in Research of Informatics (INNOVATICS) Humanism : Jurnal Pengabdian Masyarakat Jurnal Pendidikan dan Teknologi Indonesia Prima Abdika: Jurnal Pengabdian Masyarakat Bulletin of Pedagogical Research Jurnal Pengabdian Pada Masyarakat Jurnal Pengabdian Informatika (JUPITA) Bulletin of Social Informatics Theory and Application Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Mohuyula : Jurnal Pengabdian Kepada Masyarakat Scientific Journal of Informatics
Herman Yuliansyah, Herman
Program Studi Teknik Informatika, Fakultas Teknologi Industri, Universitas Ahmad Dahlan
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Journal : Scientific Journal of Informatics

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MoLLe: A Hybrid Model for Classifying Diseases in Chili Plants Using Leaf Images Khoirunnisa, Itsnaini Irvina; Fadlil, Abdul; Yuliansyah, Herman
Scientific Journal of Informatics Vol. 12 No. 3: August 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i3.29071

Abstract

Purpose: Leaf diseases are often early indicators of problems in plants. More detailed image information with feature extraction on leaves can improve accuracy. However, MobileNetV2 tends to be less than optimal in capturing the fine texture characteristics of leaves. This research aims to propose a classification model for diseases in chili plants based on leaf images using MobileNetV2 with Local Binary Pattern (LBP), with three fully connected layers (220-120-60 neurons) using the ReLU activation function, referred to as MoLLe. Methods: This research consists of six stages. It begins with a dataset collected from chili farms comprising 900 images, which are then preprocessed into 3,600 images. Next, LBP feature extraction is performed. After that, a comparison between the benchmark architecture and the proposed architecture is conducted. A softmax layer is used to perform three-class classification. The MoLLe model was tested with the MobileNetV2 and MobileNetV2+LBP benchmark architectures and evaluated using a confusion matrix. Result: Based on the evaluation conducted, using batch size 32, learning rate 0.001, and 20 epochs, the MoLLe model experienced early stopping at epoch 11, achieving an accuracy of 0.97 training data, 0.84 validation data, and 0.91 testing data. The evaluation results showed consistent precision, recall, and F1-score values of 0.91, indicating the model's balanced ability to identify the three disease classes. Novelty: The novelty of this research lies in the integration of MobileNetV2 and LBP with modifications to three fully connected layers, which not only reduces the number of training parameters but also accelerates the detection process. This research makes an essential contribution to the development of more efficient and effective plant disease detection systems, with experimental results showing that MoLLe outperforms the benchmark architecture.
Co-Authors Abdul Fadlil Adhi Prahara, Adhi Agus Setiawan, Hisyam ALYA MASITHA Anton Yudhana Apriliani, Evinda Ardiansyah, Ricy Arief Ghozali, Fanani Asti Mulasari, Surahma Ayu Laksmi Pandhita, Ayu Laksmi Bambang Sudarsono Bella Okta Sari Miranda Bidinnika, Muhammad Kunta Darmanto Darmanto Destriana, Rachmat Dewi Soyusiawaty Dewi, Ayu Intansari Donna Setiawati Eko Hari Rachmawanto Fatwa Tentama Febiyan, Rifal Firdaus, Muhammad Khysam Fitriani Mutmainah, Nur Fitriani, Isah Ghozali, Fanani Arief Habie, Khairul Fathan Hafin, Aqid Fahri Hazar, Siti Herman Herminarto Sofyan Hidayat, Muhammad Taufiq Hildayanti, Ica Kurnia Hildayanti, Ica Kurnia Ika Arfiani Imam Riadi Irfan, Syahid Al Jayawarsa, A.A. Ketut Jefree Fahana Jumaedi Nasir, Ardiansyah Khoirul Anam Dahlan Khoirunnisa, Itsnaini Irvina Kintung Prayitno, Kintung Lifa, Lifa Lina Handayani Listyaningrum, Prabandari Mahiruna, Adiyah Muhammad Abdul Aziz Muhammad Dzikrullah Suratin, Muhammad Dzikrullah Muhammad Fahmi Mubarok Nahdli Muhammad Kunta Biddinika Muhammad Ridwan Murinto Murinto Murinto Mutmainah, Nur Fitri Nafiati, Lu'lu' Nafiati, Lu’lu’ NGATIMIN, NGATIMIN Nia Ekawati, Nia Nisa Novianti, Tria Novitasari, Isda Desy Nur Rochmah Dyah Pujiastuti Pamungkas, Gilang Pamungkas, Gilang Pratama, Ridho Haikal Pratama, Wegig Putro, Aldibangun Pidekso R. Hafid Hardyanto, Settings Rachmaliany, Nur Rahmawan, Jihad Rahmawati, Rahmawati Raihan, Habib Aulia Rajunaidi, Rajunaidi Razak, Farhan Radhiansyah Rohmadi, Yusuf Eko Rusydi Umar Salji, Rinday Zildjiani Sri Winiarti Subardjo Subardjo, Subardjo Sukesi , Tri Wahyuni Sulistyawati , Sulistyawati Sulistyawati Sulistyawati Sunardi Sunardi Sunardi Surahma Asti Mulasari Tole Sutikno Tri Wahyuni Sukesi Ulumiyah, Iftitah Dwi Wahyuni Sukesi, Tri Wala, Jihan Wan Ali, Wan Nur Syamilah Yohanni Syahra Yulianto, Dinan Yulisasih, Baiq Nikum