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Nominal Detection of Rupiah Banknotes with Audio Output Using MobileNetV2 Transfer Learning Method

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 19 No. 1 (2026) · pp. 99–106

DOI
10.21609/jiki.v19i1.1674
ISSN
2502-9274, 2088-7051
Published
2026-03-02
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Banknotes are widely used all over the world. Banknotes are a means of payment used by the public, including the visually impaired. The visually impaired still depend on others to recognize the nominal rupiah banknotes. One of the efforts that can help the visually impaired is creating a machine-learning model that can recognize the nominal rupiah banknotes. This research aims to assist the visually impaired in independently identifying the nominal rupiah banknotes. In this study, the MobileNetV2 pre-trained model was used to learn how to make a model that can detect the nominal amount of rupiah banknotes. The dataset consisted of 1,400 images of rupiah banknotes, divided into 80% for training data and 20% for testing data. The evaluation carried out on the model using the confusion matrix resulted in a model accuracy value of 99.2%.

Collaboration network of the authors

2 authors · 1 co-authorship link

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Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Nominal Detection of Rupiah Banknotes with Audio Output Using MobileNetV2 Transfer Learning Method</dc:title>
	<dc:creator>Farid Abdillah, Rachmat</dc:creator>
	<dc:creator>Ramadhani, Dian</dc:creator>
	<dc:description xml:lang="en-US">Banknotes are widely used all over the world. Banknotes are a means of payment used by the public, including the visually impaired. The visually impaired still depend on others to recognize the nominal rupiah banknotes. One of the efforts that can help the visually impaired is creating a machine-learning model that can recognize the nominal rupiah banknotes. This research aims to assist the visually impaired in independently identifying the nominal rupiah banknotes. In this study, the MobileNetV2 pre-trained model was used to learn how to make a model that can detect the nominal amount of rupiah banknotes. The dataset consisted of 1,400 images of rupiah banknotes, divided into 80% for training data and 20% for testing data. The evaluation carried out on the model using the confusion matrix resulted in a model accuracy value of 99.2%.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2026-03-02</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1674</dc:identifier>
	<dc:identifier>10.21609/jiki.v19i1.1674</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 19 No. 1 (2026): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 99-106</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v19i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1674/557</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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