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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Informatika Upgris
Supriyanto, Kus
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Computer Science & IT

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PENGEMBANGAN APLIKASI ESTIMASI KALORI MAKANAN BERBASIS CITRA DENGAN PENDEKATAN DETEKSI OBJEK MENGGUNAKAN YOLO Supriyadi, Rizqy; Irfan, Muhamad; Hapijar, Rizki Dwi; Abubakar, Fadil; Saputra, Rendy; Supriyanto, Kus; Dwiantara, Raihan Putra; Nainggolan, Esron Rikardo; Brawijaya, Herlambang
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 1 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i1.8545

Abstract

Penelitian ini mengembangkan aplikasi estimasi kalori makanan berbasis citra untuk membantu pengguna memantau asupan energi secara praktis melalui foto ponsel. Sistem menggunakan deteksi objek YOLOv8n untuk mengenali makanan Indonesia dan memetakan tiap deteksi ke parameter nutrisi guna menghitung massa dan kalori. Dataset pelatihan berisi 3.772 citra pada 9 kelas makanan (dibagi 80% latih, 10% validasi, 10% uji). Model dilatih selama 100 epoch pada resolusi 640 piksel menggunakan optimizer AdamW dan early stopping. Backend FastAPI dalam lingkungan Docker menjalankan inferensi dan perhitungan kalori berdasarkan data nutrisi tiap kelas. Aplikasi mobile Flutter mengirim citra ke endpoint /predict dan menampilkan makanan terdeteksi beserta confidence, estimasi massa, dan total kalori. Hasil uji menunjukkan performa deteksi tinggi dengan mAP@0.5 0,975, sementara kesalahan terbesar terjadi pada kelas yang mirip secara visual atau minim data. Temuan ini menegaskan bahwa sistem end-to-end mampu mengestimasi kalori otomatis dari satu foto dan layak dikembangkan lebih lanjut dengan menambah kelas dan menyeimbangkan dataset.
Implementasi Algoritma Huffman Coding pada Sistem Kompresi Citra Digital Berbasis Web Supriyadi, Rizqy; Saputra, Rendy; Abubakar, Fadil; Hapijar, Rizki Dwi; Dwiantara, Raihan Putra; Supriyanto, Kus; Irfan, Muhamad; Indriyani, Luthfi; Nainggolan, Esron Rikardo
Jurnal Informatika UPGRIS Vol 12, No 1: Juni 2026
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v12i1.27618

Abstract

Abstract— The rapid development of digital technology has increased the need for efficient storage and transmission of digital images. Large image file sizes can affect storage efficiency and data transfer processes, making image compression techniques necessary to reduce file size without significantly decreasing visual quality. This research aims to implement a web-based digital image compression system using a combination of Discrete Cosine Transform (DCT), quantization, Run Length Encoding (RLE), and Huffman Coding methods. The system was developed using the Laravel framework with support from HTML, CSS, and JavaScript, while image processing was performed using the canvas element in the browser. The compression process consists of RGB splitting, 8×8 blocking, DCT transformation, quantization, zigzag scanning, RLE, and Huffman Coding. The system also provides a before-after slider feature and evaluation parameters including Compression Ratio, Mean Squared Error (MSE), and Peak Signal-to-Noise Ratio (PSNR). Based on testing results using several JPG/JPEG images, the system achieved compression ratio values ranging from 79% to 97% with PSNR values between 31 dB and 38 dB. These results indicate that the proposed methods are capable of significantly reducing image file size while maintaining good visual quality.
Co-Authors Abubakar, Fadil Dwiantara, Raihan Putra Hapijar, Rizki Dwi Herlambang Brawijaya Irfan, Muhamad Luthfi Indriyani Nainggolan, Esron Rikardo Rendy Saputra Supriyadi, Rizqy