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All Journal Jurnal Teknik Informatika UNIKA Santo Thomas JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Teknologi Informasi MURA JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Teknologi Informasi Mura Adpebi Science Series Jurnal UNIV.BI MENGABDI
Irvai, Muhammad
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SEGMENTASI MULTIKELAS PENYAKIT DAUN KENTANG MENGGUNAKAN ARSITEKTUR U-NET DENGAN PRE-TRAINED EFFICIENTNET Putriani, Shella Ayu; Akbar, Muhamad; Irvai, Muhammad; Karman, Joni
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 11 No 1 (2026): JUTIM (Jurnal Teknik Informatika Musirawas) Maret
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jutim.v11i1.2931

Abstract

Deep learning is widely used to support precise visual analysis. This study aims to analyze and compare the performance of potato leaf image segmentation models using the standard U-Net architecture and U-Net with EfficientNet-B0 through a transfer learning approach. The dataset used consists of 3000 potato leaf images along with segmentation masks obtained from secondary data sources with a division of 1000 per class, then divided into training, validation, and testing data. The research stages include data preprocessing and augmentation, segmentation modeling, model training, and model performance evaluation. Evaluation is carried out using intersection metrics such as Intersection over Union (IoU), mean IoU (mIoU), and Dice Coefficient, with a confusion matrix as an additional analysis tool. The implementation of this study uses the Python programming language supported by the TensorFlow and Keras frameworks, and is run on the Google Colab environment. The results of this study are expected to show the performance differences between the standard U-Net and U-Net with EfficientNet-B0, thereby providing an overview of a more optimal segmentation model for potato leaf image analysis.
Co-Authors Daulay, Nelly Khairani Dwi Budi Santoso Efranda, Nolan Intan, Bunga Karman, Joni Mahdalena, Desi Muhamad Akbar Nopalia, Nopalia Putriani, Shella Ayu Rizki, Fido Rusdiyanto Rusdiyanto, Rusdiyanto Susanto Susanto