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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

Android-based Detection of Melon Leaf Diseases Using Convolutional Neural Network and TensorFlow Syahputri, Rahmalia; Winarto; Trisnawati, Sherli; Taufik
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.14542

Abstract

Melon productivity in Indonesia has experienced a significant decline due to leaf diseases, while manual detection performed by farmers remains subjective, time-consuming, and highly dependent on individual experience. To address this issue, this study aims to develop a mobile-based melon leaf disease detection system utilizing a Convolutional Neural Network (CNN) architecture integrated into the Tani Cerdas Android application via the TensorFlow framework. The dataset consists of 250 images of melon leaves categorized into five classes: healthy, aphids, fusarium wilt, leaf caterpillars, and unknown. Data were collected from two different melon farms employing distinct cultivation methods and processed through the machine learning life cycle, including data cleaning, manual labeling using one-hot encoding, splitting into 80% training and 20% validation sets, model training, and performance evaluation. The CNN model was trained for 11 epochs using ReLU and Softmax activation functions and a dropout rate of 0.2 to reduce the risk of overfitting. Training results achieved an accuracy of 91.5% with a loss value of 0.313, while model validation reached 71.9% accuracy. The ROC-AUC evaluation indicated excellent classification performance in most classes (AUC 0.99–1.00), although performance in the fusarium wilt class remained lower (AUC 0.87). Deployment of the model into the Tani Cerdas application achieved an average field accuracy of 86.33%. This study demonstrates the effectiveness of CNN and TensorFlow integration in supporting rapid and independent detection of melon leaf diseases via mobile devices, offering potential for the development of similar systems for other horticultural commodities.
Co-Authors Achmad Ma’arif Saefuddin Agus Suratno Agus Widyianto Amaliah, Khusnatul Andhika Guna Dharma Ardiansyah, Aqib Arnila Novitasari Saubig Arum Ningtyas, Rizki Arumi Sintiara Asri Widowati Ayu Retnoningsih, Diyah Azizah Basabih, Masyitoh Bella Fangbethia Budi Luwar Sanyoto Chandra Utami Wirawati Chasan Azari Chazan Azari Dwi Eva Nirmagustina Dyah Khairunnisa, Ananda Ebib Eddy Bagus Wasito Edi Irwanto Ekosari Roektiningroem Endang Sulistyani Fahmi, Muhammad Ruslan Zamzami Faris Arromal, Muhammad Febrina Hambalah Febrina Indrasari Firdian, Muhammad Syukron Fitra Fitriani Giovanni, Lawrenzia Herman HERMAWAN Hesty Kristyaningrum, Dwi I'tishom, Reny Iga Kalaringga Jambose Indriani Tiara Hastari Isnaini Nurkhayati Jati Nugroho Jumi Khoerunnisa, Tiara Kurnia Liza Rusdiyana Maharani Mahirul Mursid Marhaeni, Sri Maulana Sidiq, Arya Mila Dia Nor Asiya Mochamad Akbar Bangkit Moeheriono Muhammad Arifianto Nasution Munthe, Pupu Sulayas Br Nabilla Aulia Nisa Nadapdap, Kristanty M N Nainggolan, Rahel Junita Nanda Istiqomah Nurbani Kalsum Nurkhayati, Isnaini Nurul Fatma Hardianti Nurwasis Nurwasis Nyilo Purnami Olivia, Jessica Orlanda Arya Hidayat Panggabean, Toman Paryanto Prety Indah Sari Puji Rahayu, Dita Puji Putri Rainy Putri, Avirdha Putut Haribowo, Putut R, Lutfi Irawan Rafa Chalesto, Arthur Rahmalia Syahputri REZA, REZA DWI ARIYANI Ridho Akbar Riska Fita Lestari Rivka Izzati Nisa Rohani Rojak, Thasya Sabilla Putri RR Laksistya Rania Nur Prita Maira S.Pd. M Kes I Ketut Sudiana . Safii Salma Nabilah Sandy, Desi Sator Sapan Bungin Saur Melianna Seia Mahanani Sigit Rimbatmojo, Sigit Siregar, Dorkas Rama Widya Sriwidati Afrilia Krisnadi Subiyanto, Hari Suhariyanto Sulistiyani, Endang Suranta, Roy Michael Surfiana Surfiana Tanijaya, Jonie Tanto Pratondo Utomo Taufik Thiyas Tono Taufiq Tiur Rajagukguk, Tiur Tri Dharma Sipayung, Tri Dharma Trisnawati, Eka Trisnawati, Sherli Winda Sefhiani Zuhria, Ismi