A Learning Vector Quantization Approach to Handwritten Mandarin Numeral Recognition

Septi Vera Soniya, Yustina Retno Wahyu Utami, Hendro Wijayanto

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.


Keywords


Learning Vector Quantization; Pattern Recognition; Mandarin Numbers

Full Text:

PDF

References


Angga Kurniawan, A., Dian Syah, R., & Ariyani, R. (2022). Klasifikasi Citra Digital Tulisan Tangan Angka Menggunakan Metode Convolutional Neural Network. JUIT, 1(1), 36–41. https://cezannec.github.io/

Daood, A., Al-Saegh, A., & Fadhil Mahmood, A. (2023). Handwriting Detection And Recognition Of Arabic Numbers And Characters Using Deep Learning Methods. In Journal of Engineering Science and Technology (Vol. 18, Number 3).

Fergina, A., Badrujaman, A., & Yustiana, I. (2022). Development of Android-Based Speech Recognition Application Using Learning Vector Quantization Method in Optimizing Deaf Communication. International Journal of Electrical Engineering and Information Technology, 05.

Handoko, A. A., Rosid, M. A., & Indahyanti, U. (2024). Implementasi Convolutional Neural Network (CNN) Untuk Pengenalan Tulisan Tangan Aksara Bima. SMATIKA JURNAL, 14(1), 96–110. https://doi.org/10.32664/smatika.v14i01.1196

Semuel, N., & Pekuwali, A. A. (2022). Pattern Recognition of Doctor’s Prescription Handwriting Using the Naïve Bayes Classifier Method at Puskesmas Kambaniru Pengenalan Pola Tulisan Tangan Resep Dokter Menggunakan Metode Naïve Bayes Classifier pada Puskesmas Kambaniru. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 2(1), 55–61.

Kaparang, G. N. (2024). Bahasa Mandarin untuk Pemula. Deepublish Digital.

Sah, A., Korespondensi, P., Desi Alexander, A., & Tanniewa, A. M. (2025). Pengembangan Model Klasifikasi Citra Penyakit Daun Lada Menggunakan Jaringan Syaraf Tiruan Learning Vector Quantization (LVQ). JURNAL ILMIAH INFORMATIKA DAN ILMU KOMPUTER (JIMA-ILKOM), 4(1), 34–44. https://doi.org/10.58602/jima-ilkom.v4i1.53

Salsabila Citra Putri Winanto, C., Intan Nuraini, A., & Ibnu Adam Informatika, R. (2025). Pengenalan Angka Pada Citra Tulisan Tangan Menggunakan Algoritma Convolutional Neural Network (CNN). In Jurnal Mahasiswa Teknik Informatika) (Vol. 9, Number 4).

Semita, M. J. (2018). Bahasa Mandarin Untuk Pemula. Pusat Kajian Bahasa.

Subagyo, I. R., & Akbar, M. (2025). Hybrid Matrik Co-Occurence Dan Learning Vector Quantization Pada Klasifikasi Citra Gelombang Suara Perut. Jurnal Mahasiswa Teknik Informatika), 9(1), 850–857.

Wicaksana, C., & Lufianawati, D. (2021). Pengenalan Pola Vektor Tanda Tangan Citra Digital Menggunakan Metode Pembagian Wilayah dan Learning Vector Quantization (LVQ). Setrum : Sistem Kendali-Tenaga-Elektronika-Telekomunikasi-Komputer, 10. https://doi.org/10.36055/setrum.v10i2.13054




DOI: http://dx.doi.org/10.30646/sinus.v24i1.1073

Refbacks

  • There are currently no refbacks.


 

STMIK Sinar Nusantara

KH Samanhudi 84 - 86 Street, Laweyan Surakarta, Central Java, Indonesia
Postal Code: 57142, Phone & Fax: +62 271 716 500 

Email: ejurnal @ sinus.ac.id | https://p3m.sinus.ac.id/jurnal/e-jurnal_SINUS/

ISSN: 1693-1173 (print) | 2548-4028 (online)

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

View My Stats