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Vivin Yulfia Sarah
System Computer, Universitas Pembangunan Pancabudi Medan
Computer Science & IT

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ANALYSIS OF K-NEAREST NEIGHBOR METHODS IN DETECTING FAKE MONEY Vivin Yulfia Sarah; Zulham Sitorus; Zulfahmi Zulfahmi
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Money plays a very important role in human life. In the history of human civilization, money has played all the roles of paper money. Not only the symbol of the state, but also a tool that can unite one country to another. It has also become an economic management tool. The Indonesian government has an Indonesian bank that has appointed a printer that specializes in printing money. Only money issued by official and legal banks in Indonesia can be used as legal tender. This research is designed to identify and verify fake and genuine banknotes. This approach consists of several steps, including image acquisition and grayscale conversion, active contour, histogram, image extraction. This study uses banknotes of Rp. 100,000; as the object of research. The results of image processing that have been carried out, it can be concluded that to detect counterfeit money or the authenticity of banknotes can be done based on the watermark on the money which can be imaged using Matlab by performing computational digital image processing, namely grayscale conversion, active contour, histogram, image extraction. The accuracy results obtained from the evaluation of the authenticity of banknotes are 98.5%.
Co-Authors Sitorus, Zulham Zulfahmi Zulfahmi