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All Journal TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal TIMES International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) BIOLINK (Jurnal Biologi Lingkungan, Industri, Kesehatan) JURNAL MEDIA INFORMATIKA BUDIDARMA JTAM (Jurnal Teori dan Aplikasi Matematika) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Mantik Indonesian Journal of Electrical Engineering and Computer Science Pelita Masyarakat Journal of Applied Data Sciences JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Science in Information Technology Letters Journal of Applied Computer Science and Technology (JACOST) International Journal of Engineering, Science and Information Technology EXPLORER Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Pada Masyarakat METHABDI Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Jurnal Pengabdian Masyarakat (Jubdimas)
Hartono Hartono
Department Of Magister Program In Informatics, Postgraduate School, Universitas Medan Area
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Analisis Komparatif CNN Ringan untuk Klasifikasi Penyakit Daun Tomat Menggunakan Visualisasi Grad-CAM Rahman, Sayuti; Hartono, Hartono; Sembiring, Arnes; Khahfi Zuhanda, muhammad; Aditya Pratama, Bayu; Martini, Dewi
Explorer Vol 6 No 1 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v6i1.2601

Abstract

Tomato leaf disease classification based on digital imagery has become an important approach in supporting smart agriculture, particularly for early detection of plant disease attacks. This study aims to compare the performance of several lightweight Convolutional Neural Network (CNN) architectures, namely MobileNetV3-Small, MobileNetV2, and EfficientNet-B0, in classifying tomato leaf diseases using the PlantVillage dataset. The dataset consists of 3,628 images distributed across 10 classes (9 disease classes and 1 healthy class), with a data split scheme of 80% for training and 20% for validation. Performance evaluation was conducted using classification reports, confusion matrices, and interpretability analysis through Grad-CAM and feature map visualization. The experimental results show that all models achieved very high accuracy, exceeding 99%. EfficientNet-B0 obtained the best performance with a validation accuracy of 99.59%, followed by MobileNetV2 at 99.45% and MobileNetV3-Small at 99.04%. However, model complexity increased along with accuracy, where EfficientNet-B0 had the largest number of parameters and FLOPs. Grad-CAM analysis revealed that higher-accuracy models demonstrated more precise activation focus on leaf lesion regions. This study confirms that lightweight CNN architectures are capable of delivering excellent classification performance while offering strong potential for deployment in plant disease detection systems on resource-limited devices
Co-Authors Aditya Pratama, Bayu Ammar Yasir Nasution Andi Rahmadsyah Andik Bintoro Andre Hasudungan Lubis Andriasan Sudarso Arnes Sembiring Asmah Indrawati B. Herawan Hayadi B. Herawan Hayadi Brilliant Handyman Manalu Citra Rahmadhani Cut Ita Erliana Dadan Ramdan Dahlan Abdullah Dedi Sahputra Desniarti Dian Maya Sari Elvie Maria Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erna Budhiarti Nababan Faadhil, Faadhil Finta Aramita Firman Syahputra Firman Syahputra Gio, Prana Ugiana Habib Satria Imelda Maelani Iqbal Giffari Ritonga Irwan Daniel Jaka Kusuma Jaka Kusuma Khairul Fadhli Margolang Limas, Agus Fahmi Maricha Elveny Marischa Elveny, Marischa Martini, Dewi Meli Handayani Mendarissan Aritonang Muhammad Ikhwani Muhammad Khahfi Zuhanda Muhammad Sadikin Muhammad Zarlis Muhammad Zulkarnain Lubis Mulkan Andika Situmorang N. Nazaruddin Nadapdap, Kristanty M. N. Nadra Ideyani Vita Nasution, Mahyuddin K.M Necia Mita Novalina Pasaribu Nos Sutrisno Nur Anzelina Nur Azelina Harahap Nursie, Aly Opim Salim Sitompul Prana Ugi Rachmat Aulia, Rachmat Rahmad B.Y Syah Rahman, Sayuti Rana Fathinah Ananda Retna Astuti Kuswardani Rezzy Eko Caraka Ria Wuri Andary Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly, Rika Rohima Rohima Rubianto Sabina Krisdayanti Samsul A Rahman Sidik Hasibuan Sembiring, Arnes Silvia Lestari Silvia Lestari Siti Aisyah Sitorus, Peniel Sam Putra Sugeng Riyadi Suswati Suswati suswati suswati Syah, Rahmad B.Y Tulus Tulus Wanayumini Wulan Dari Yeni Risyani Yudi Gebri Foenna Zakarias Situmorang