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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Gede Made Widi Anditya
Universitas Udayana
Computer Science & IT Engineering

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Klasifikasi Kematangan Tomat pada Citra Digital Menggunakan DeiT (Data-efficient Image Transformer) I Gede Made Widi Anditya; Gst. Ayu Vida Mastrika Giri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 4 (2025): JNATIA Vol. 3, No. 4, Agustus 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v03.i04.p03

Abstract

This study addresses the critical need for accurate and efficient tomato ripeness classification in agriculture and agribusiness, aiming to overcome the limitations of subjective manual methods. Leveraging advances in Computer Vision, this study implements a Data-efficient Image Transformer (DeiT) model for automatic classification of digital tomato images. DeiT, a Transformer-based architecture developed by Facebook AI Research, was chosen for its superior performance on small to medium-sized datasets, leveraging knowledge distillation. The model was trained using the Kaggle dataset, instrumented to enhance visual diversity, to classify tomatoes into “ripe” and “unripe” categories. Evaluation was performed using standard classification metrics including accuracy, F1-Score, and confusion matrix. The model demonstrated high performance, achieving an overall accuracy of 0.96 on the test dataset.
Co-Authors Gst. Ayu Vida Mastrika Giri