CD Skripsi

Klasifikasi Gambar Makanan Pada Aplikasi Berbagi Makanan Menggunakan Metode Deep Learning

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ABSTRACT
Food waste in the world has become a very big issue in various countries. According to the Food and Agricultural Organization (FAO), 1.3 billion tons of edible food annually is wasted. The Food and Agricultural Organization (FAO) said that Indonesia is in second place as the world's largest producer of food waste, namely 300 kg per person per year. At the same time, Indonesia is included in the moderate category on the global hunger index and is ranked 73 out of 116 countries in 2021. To overcome this problem an application is needed that functions as a link between people who want to share their leftover food and people who need food. In making a sharing food application, it is inseparable from making a backend and frontend. On the frontend, a user interface is made that is useful for users to interact with the system. In the backend of this food sharing application, a food image classification is made which can detect images in the form of food images and non-food images. This Food Image Classification was created using the Deep Learning method with the Convolutional Neural Network (CNN) algorithm and the ResNet-50 Architecture. To know the performance of the model. To find out the performance of the model, it is necessary to test it using the Confusion Matrix, which calculates accuracy, precision and recall. The results of this study obtained an accuracy of 97%, 99% precision, 96% recall and 97% F1-Score. To obtain accuracy, precision, recall, and F1-Score values obtained by measuring using testing data with the ResNet 50 architecture that has been trained.
Keywords : Deep learning, CNN, ResNet 50, Food Waste, Image Classification

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1807113673

Penerbit

Pekanbaru : Universitas Riau – Fakultas Teknik – Teknik Informatika., 2022

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1807113673

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

TEKNIK ELEKTRO

Info Detail Spesifik

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Pernyataan Tanggungjawab

DAUS

Versi lain/terkait

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