OKTAL : Jurnal Ilmu Komputer dan Sains
Vol 4 No 12 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains

Klasifikasi Gambar Makanan Indonesia Menggunakan Algoritma CNN

Palgunadi (Unknown)
Reinardus Di Caprio Kadju (Unknown)
Wisnu Kuntjoro Adji (Unknown)
Perani Rosyani (Unknown)



Article Info

Publish Date
26 Dec 2025

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.

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Journal Info

Abbrev

oktal

Publisher

Subject

Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

Description

1. Komputasi Lunak, 2. Sistem Cerdas Terdistribusi, Manajemen Basis Data, dan Pengambilan Informasi, 3. Komputasi evolusioner dan komputasi DNA/seluler/molekuler, 4. Deteksi kesalahan, 5. Sistem Energi Hijau dan Terbarukan, 6. Antarmuka Manusia, 7. Interaksi Manusia-Komputer, 8. Hibrida dan ...