Klasifikasi Ras Mongoloid Berbasis Citra Wajah menggunakan Algoritma k-Nearest Neighbors

Authors

  • Febryanti Sthevanie Universitas Telkom
  • Kurniawan Nur Ramadhani Universitas Telkom
  • Hafidh Fikri Rasyid Universitas Telkom

DOI:

https://doi.org/10.21108/INDOJC.2018.3.1.212

Abstract

Pada penelitian ini dibangun sistem untuk mengklasifikasi ras Mongoloid dan non-Mongoloid berdasarkan daerah periorbital wajah. Penelitian ini menggunakan metode ekstraksi ciri Local Binary Pattern (LBP) dan algoritma klasifikasi k-Nearest Neighbors (k-NN). Penelitian ini menggunakan citra wajah dari 996 individu berbeda. Dari penelitian ini, didapatkan konfigurasi parameter terbaik untuk algoritma LBP yaitu nilai P=8, R=4 dan ukuran grid 5x5. Sedangkan untuk k-NN didapatkan nilai optimal untuk parameter k=5. Nilai akurasi terbaik yang didapatkan pada sistem klasifikasi ras ini  menggunakan metode LBP dan k-NN adalah sebesar 91,88%.

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Published

2018-05-23

How to Cite

Sthevanie, F., Ramadhani, K. N., & Rasyid, H. F. (2018). Klasifikasi Ras Mongoloid Berbasis Citra Wajah menggunakan Algoritma k-Nearest Neighbors. Indonesian Journal on Computing (Indo-JC), 3(1), 45–54. https://doi.org/10.21108/INDOJC.2018.3.1.212

Issue

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

Section

Computer Science

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