Sistem Pengenalan Wajah pada Sistem KYC dengan Algoritma Local Binary Pattern Histogram

Authors

  • Hafidz Ubaidillah Universitas Muhammadiyah Gresik
  • Henny Dwi Bhakti Universitas Muhammadiyah Gresik

DOI:

https://doi.org/10.55606/juitik.v4i1.754

Keywords:

KYC, Face Recognition, API, Local Binary Pattern Histogram Algorithm

Abstract

With the increasing internet usage post-pandemic, ensuring the security of a fintech application becomes imperative. Bangbeli implements KYC procedures using facial recognition technology and stringent security protocols to verify identities and safeguard users' personal data in compliance with Bank Indonesia regulations. Utilizing Haar Cascade Classifier, Local Binary Pattern Histogram, and histogram equalization, an API (Application Programming Interface) has been created for facial training and prediction. These methods were chosen for their credibility, achieving an 88% accuracy with 33 samples and 90% with 10 samples. This study focuses on constructing an API for mobile services at Bangbeli, achieving 87.5% accuracy, 81.25% precision, 87.5% recall, and a 25% error rate. The model demonstrates good performance in facial recognition, with an acceptable error rate. Although precision is slightly lower than recall, it suggests the model is more inclined to identify most positive data with some errors rather than discard potentially identifiable faces.

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Published

2024-01-08

How to Cite

Hafidz Ubaidillah, & Henny Dwi Bhakti. (2024). Sistem Pengenalan Wajah pada Sistem KYC dengan Algoritma Local Binary Pattern Histogram. Jurnal Ilmiah Teknik Informatika Dan Komunikasi, 4(1), 141–154. https://doi.org/10.55606/juitik.v4i1.754

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