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Journal : Jurnal Teknik Informatika (JUTIF)

Enhanced U-Net Cnn For Multi-Class Segmentation And Classification Of Rice Leaf Diseases In Indonesian Rice Fields Faturrohman, Faturrohman; Nurdiawan, Odi; Prihartono, Willy; Herdiana, Rully
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5258

Abstract

Rice is a strategic food crop whose productivity is often threatened by leaf diseases and pests. This study aims to develop an Enhanced U-Net CNN model for multi-class segmentation and classification of rice leaf conditions from field images to support early detection and plant health management. The methodology includes direct field image acquisition of rice leaves, preprocessing for image quality enhancement, expert data labeling, segmentation using a U-Net architecture, and classification using CNN. The dataset was divided into training and testing data with balanced distribution across four classes: Healthy, BrownSpot, Hispa, and LeafBlast. Evaluation results show that the model can identify rice leaf conditions with high accuracy, although signs of overfitting were observed from the performance gap between training and validation data. The implementation of this model is expected to accelerate automatic disease detection in the field, reduce reliance on manual inspection, and support precision agriculture. This study achieved a testing accuracy of 76.36% with a macro-average F1-score of 0.34. While the results indicate limitations in generalization, the proposed Enhanced U-Net CNN demonstrates the feasibility of combining segmentation and classification in field conditions. This research contributes to agricultural informatics by supporting scalable deployment in precision agriculture systems, reducing reliance on manual inspection, and providing a foundation for further optimization studies.
Co-Authors ., Fathurrohman Agustin, Nia Aini Nurul Ainisa, Nurul Al Lutfani, Thariq Kemal Al Maeni, Nurul Amelia, Astri Ameliana, Nikan Andre Setiawan, Andre Apriliansyah, Rizal Dwi Rizki Aprilla, Anggita Arifqi, Tri Astuti , Rini Ayu Azzahra, Fadita Ayuni, Putri DAIPAH, IIP IMRON Dalifah, Nurul Dita, Fio Eka Permana, Sandy Erpian, Soni Fachry Abda El Rahman Fathur Rohman, Fathur Fathurrohman Fathurrohman Faturrohman, Faturrohman Faujia, Agnes Firmansyah, Fajar Gifthera Dwilestari Gunawan, Sepriyan Hadi Wicaksana, Arya Haikal, Harisman Hamonangan, Ryan Haryandini, Nur Anindya Putri Hayati, Umi Herdiana, Rulli Herdiana, Rully Hidayah, Nurni Hidayat, Pierre Galuh HIDAYATULLAH, NAUFAL ARIF Hoeriah, Dede Ilham Syahputra, Arief Irfan Ali, Irfan Irma Purnamasari, Ade Jannah, Nursuviyani Jihan, Aminatun Julianti, Okta Nur Kholifa, Nur Kusmawanti, Nisa Laksamana, Patria Gita Lita, Arlita lita Maulana, Aldi Maulida, Nida Muharromah, Oom Nining Rahaningsih Nur Amalia, Ocsana Nur Apriliani, Nur Nur Kirana, Anita Nur Pangestika, Fanny Nurdin Nurhakim, Bani Nurhayah, Nurhayah Nuri Nuri Nurjanah, Nurul Nurliana, Nicky NURUL AZIZAH Nurwanda, Nurwanda Nurzaman Nurzaman Odi Nurdiawan OKTAVIANI, ERNA Oktaviany, Nurul Optarina, Yasni Peni Peni Permana, Sandy Eka PUJI LESTARI Putri Nabilla Putriana, Puput RAHMAWATI, RULI Ramadhan, Niko Retnasari, Peni Rini Astuti RIZKI, ALVA FAUZIR Rohmat, Cep Lukman Rosiana, Rosa Sakarias Berek, Richardus Salsabila, Fauhan saninah, annisa Saniyah, Nilta Sayuti Hanapiah, Neneng Suarna, Nana Yudhistira Arie Wijaya Yuslia Devitri Zaelani, Nursehan