CD Skripsi

Klasifikasi Uang Rupiah Kertas Tidak Layak Edar Menggunakan CNN XCEPTION Transfer Learning Berbasis Website

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Indonesian Rupiah banknotes are one of the legitimate means of payment in Indonesia and are also a favorite choice for everyday transactions among the Indonesian population. This high circulation of Indonesian Rupiah banknotes has led to a significant issue, which is the lack of care and maintenance by the public. Due to the public's lack of understanding regarding the condition of their banknotes, it is not uncommon to find worn-out, torn, or even unusable banknotes. In response to this problem, Bank Indonesia has launched the "Love, Pride, and Understanding of the Rupiah" educational campaign to help the public understand how to recognize, care for, and maintain their Rupiah banknotes. To address this issue, a system titled "Classification of Unfit Indonesian Rupiah Banknotes Using CNN Xception Transfer Learning on a Website-Based Platform" has been developed. This system utilizes deep learning technology with the Transfer Learning method and a dataset consisting of 14 classes, including 7 fit banknote denominations and 7 unfit banknote denominations. The goal is to classify and detect the fitness of Indonesian Rupiah banknotes. After the training process, a model with an accuracy of 99% in training, 96% in validation, 94% in testing, 92% in verification has been achieved.

Keywords - Indonesian Rupiah Banknotes, Unfit for Circulation, Xception, Transfer Learning.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1907155688

Penerbit

Pekanbaru : Universitas Riau - F. Teknik - Teknik Elektro., 2023

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1907155688

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

Vina

Versi lain/terkait

Lampiran Berkas

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