Identify The Authenticity of Rupiah Currency Using K Nearest Neighbor (K-NN) Algorithm

Authors

  • Dian Nova Kusuma Hardani Universitas Muhammadiyah Purwokerto http://orcid.org/0000-0001-5201-4912
  • Thomi Luthfianto Universitas Muhammadiyah Purwokerto
  • Muhammad Taufiq Tamam Universitas Muhammadiyah Purwokerto

DOI:

https://doi.org/10.26555/jiteki.v5i1.13324

Keywords:

Identification, Rupiah, GLCM, K-NN

Abstract

The rupiah currency is a valid exchange rate used in transactions in the Republic of Indonesia. The Rupiah is often falsified as paper currency. Rupiah paper has a unique texture characteristic so that if processed digitally, it will be easy to distinguish from fake ones.  Designing the authenticity of Rupiah currency system using the K-NN method aims to facilitate the authenticity of the currency and test the accuracy of the method used. The method used in this research is the method of Gray Level Co-occurrence Matrix (GLCM) as a method of feature extraction and K-Nearest Neighbor (K-NN) algorithm used in the identification process. The testing phase uses data for 18 currency images. The results showed an accuracy rate of 100% for the value k = 1, 77.78% for the value k = 3, and 55.56% for the value k = 5. The highest level of accuracy in a currency authenticity identification system occurs when the value of k = 1 is 100%. The value of k on the classification input using the K-NN can determine the level of accuracy of the classification process.

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Published

2019-07-11

How to Cite

[1]
D. N. K. Hardani, T. Luthfianto, and M. T. Tamam, “Identify The Authenticity of Rupiah Currency Using K Nearest Neighbor (K-NN) Algorithm”, J. Ilm. Tek. Elektro Komput. Dan Inform, vol. 5, no. 1, pp. 1–7, Jul. 2019.

Issue

Vol. 5 No. 1 (2019): June

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Articles

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