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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Wisnu Kuntjoro Adji
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Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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Klasifikasi Gambar Makanan Indonesia Menggunakan Algoritma CNN Palgunadi; Reinardus Di Caprio Kadju; Wisnu Kuntjoro Adji; Perani Rosyani
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 4 No 12 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

This study aims to classify images of traditional Indonesian foods using the Convolutional Neural Network (CNN) algorithm. Image-based food classification plays an important role in the development of visual recognition systems, particularly in the fields of food technology and artificial intelligence. The dataset used in this study consists of several classes of Indonesian foods obtained from open sources and categorized based on food types. The research process includes data collection, image preprocessing, CNN model training, and performance evaluation using accuracy metrics. The experimental results show that the CNN algorithm is able to classify Indonesian food images with good accuracy. This study is expected to serve as a foundation for the development of automatic food classification systems and to support the application of image processing technology in the Indonesian culinary field.
Co-Authors Palgunadi Perani Rosyani Reinardus Di Caprio Kadju