Pengenalan Angka Tulisan Tangan Menggunakan Diagonal Feature Extraction dan Artificial Neural Network Multilayer Perceptron

Authors

  • M. Ardi Firmansyah Universitas Telkom
  • Kurniawan Nur Ramadhani Universitas Telkom
  • Anditya Arifianto Universitas Telkom

DOI:

https://doi.org/10.21108/INDOJC.2018.3.1.214

Abstract

Pada  penelitian  ini  dibangun  sistem pengenalan angka tulisan tangan menggunakan metode ekstraksi ciri diagonal  dan  Artificial Neural Network Multilayer Perceptron. Pada ekstraksi ciri diagonal, citra dibagi menjadi beberapa area yang sama besar. Pada tiap area dihitung rata-rata nilai piksel pada setiap diagonalnya kemudian dirata-ratakan untuk mendapatkan nilai ciri pada area tersebut.  Ciri diagonal dikombinasikan dengan nilai rata-rata horizontal dan  vertikal  pada  matriks  area  tersebut  untuk  memperkuat  informasi  pada citra. Metode  ini  mencapai  akurasi  sebesar  92.80%  pada  tahap  pengujian menggunakan  1000  dataset  C1  dan  92.60%  pada  tahap  pengujian  menggunakan 1000 dataset MNIST. Kombinasi fitur diagonal dan rata-rata horizontal menghasilkan akurasi tertinggi dalam mengenali angka tulisan tangan.

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References

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Published

2018-05-23

How to Cite

Firmansyah, M. A., Ramadhani, K. N., & Arifianto, A. (2018). Pengenalan Angka Tulisan Tangan Menggunakan Diagonal Feature Extraction dan Artificial Neural Network Multilayer Perceptron. Indonesian Journal on Computing (Indo-JC), 3(1), 65–74. https://doi.org/10.21108/INDOJC.2018.3.1.214

Issue

Vol. 3 No. 1 (2018): Maret, 2018

Section

Computer Science

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