CD Skripsi

Implementasi Deep Learning Untuk Klasifikasi Jenis Sampah Organik Dan Anorganik Menggunakan Transfer Learning Vgg16

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ABSTRACT
Waste refers to objects that are no longer used, have no utility, are undesirable, or are deliberately discarded. Waste is generated from human activities and does not occur naturally. At the national level, Indonesia faced a waste emergency in 2022, marked by a total waste volume reaching 36.19 million tons. Of this amount, approximately 35.99%, or around 13,025,812.81 tons, was unmanaged waste. One effort that can aid in waste management is developing a machine learning model capable of recognizing waste types. In this study, a pre-trained VGG16 model was utilized as the foundation for creating a model that can detect waste types. The resulting model achieved an accuracy of 94.67%, while the validation score was 91.3%. The trained model demonstrated optimal performance in detecting waste types.
Kata kunci : Waste, Pre-trained model, VGG16

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2007113761

Penerbit

Pekanbaru : Universitas Riau – fakultas Teknik- Teknik elektrok., 2024

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2007113761

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 ELETROK

Info Detail Spesifik

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Pernyataan Tanggungjawab

daus

Versi lain/terkait

Lampiran Berkas

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