A Learning Vector Quantization Approach to Handwritten Mandarin Numeral Recognition

Authors

  • Septi Vera Soniya
  • Yustina Retno Wahyu Utami (SINTA ID : 5979352, Scopus ID: 56595065800) Universitas Tiga Serangkai
  • Hendro Wijayanto Universitas Tiga Serangkai

DOI:

https://doi.org/10.30646/sinus.v24i1.1073

Keywords:

Learning Vector Quantization, Pattern Recognition, Mandarin Numbers

Abstract

Numbers 1 to 10 in Mandarin are also studied in the Mandarin language learning process as basic numbers. Mandarin numbers have a different shape from Arabic numbers and Roman numerals. So it is necessary to recognize the pattern of mandarin numbers to help the learning process of mandarin. Therefore, the purpose of this research is to build an application that applies the Learning Vector Quantization method for handwriting pattern recognition of Mandarin numbers. System testing methods used are Black Box and Confusion Matrix for accuracy testing methods. The application that has been made produces an accuracy of 92.80% with a total of 250 test data. Keyword: Learning Vector Quantization, Pattern Recognition, Mandarin Numbers.

References

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Published

2026-02-06

How to Cite

Soniya, S. V., Wahyu Utami, Y. R., & Wijayanto, H. (2026). A Learning Vector Quantization Approach to Handwritten Mandarin Numeral Recognition. Jurnal Ilmiah SINUS, 24(1), 35–44. https://doi.org/10.30646/sinus.v24i1.1073

Issue

Vol. 24 No. 1 (2026): Vol. 24 No. 1, Januari 2026

Section

Articles

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