IDENTIFIKASI TELAPAK TANGAN MENGGUNAKAN METODE EKSTRAKSI CIRI PRINCIPAL COMPONENT ANALYSIS (PCA) DAN IDENTIFIKASI CIRI RESILIENT PROPAGATION

  • Mellanie Lette(1)
    Universitas Nusa Cendana
  • Adriana Fanggidae(2*)
    Universitas Nusa Cendana
  • Nelci D Rumlaklak(3)
    Universitas Nusa Cendana
  • (*) Corresponding Author
Keywords: palmprint, resilient propagation, principal component analysis, error tolerance, neuron hidden, neuron output

Abstract

 The palmprint recognation in this research was being held through several stages, which are image acquisition, preprocessing using histogram equalization,edge detection using sobel operation, feature extraction  using Principal Componnent Analysis and face identification using Resilient Propagation. This research use Principal Componnent Analysis as its feature extraction method and Resilient Propagation as its recognition method. This research use 40 training data and 20 testing data wich are gained from PolyU. The final result of the research shows that accuration performance of system using Principal Componnent Analysis and Resilient Propagation by using error tolerance as 1,E-06 and neuron hidden output as 10 are giving best performation that is 65% can be recognized as compared with using the othe error tolerance , neuron output and neuron hidden .

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References

[1] Putra, 2008, Sistem Biometrika, Andy, Yogyakarta.
[2] Sari, R. N., 2014, Analisis dan Perancangan Pengamanan Data Pada Citra Digital dengan Algoritma Least Significant Bit (LSB).
[3] Amelia, L. , Marwati, M., 2013, Perbandingan Metode Roberts dan Sobel dalam mendeteksi tepi suatu citra digital.
[4] Ulumiyah, D., 2009, Pengenalan Telapak Tangan menggunakan Naïve Bayes berbasis Reduksi Dimensi PCA.
[5] Kusumadewi S., 2003, Artificial Intelligence (Teknik dan Aplikasinya), Graha Ilmu, Yogyakarta
[6] Arkiang A., 2015, Identifikasi Tanda Tangan Offline Menggunakan Local Binary Pattern 8 Rotasi Dengan Pembelajaran Resilient Propagation, Skripsi, Jurusan Ilmu Komputer Fakultas Sains dan Teknik, Universitas Nusa Cendana, Kupang
[7] Braun H. dan Riedmiller M., 1993, A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm, IEEE, Vol. 1, 586-591.

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Published
2021-09-19
How to Cite
[1]
M. Lette, A. Fanggidae, and N. Rumlaklak, “IDENTIFIKASI TELAPAK TANGAN MENGGUNAKAN METODE EKSTRAKSI CIRI PRINCIPAL COMPONENT ANALYSIS (PCA) DAN IDENTIFIKASI CIRI RESILIENT PROPAGATION”, jicon, vol. 4, no. 1, pp. 52-61, Sep. 2021.
Section
Articles

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