Face Recognition using Webcam with K Nearest Neighbors Algorithm for Employee Presence

 (*)Nurul Akbar Tanjung Mail (Perbanas Institute, Jakarta, Indonesia)
 Sanwani Sanwani (Universitas Nusa Mandiri, Indonesia)

(*) Corresponding Author

Submitted: November 13, 2021; Published: November 30, 2021

Abstract

Attendance is an activity to store data related to employee attendance. Therefore, it is necessary to have a presence with a biometric identification system such as facial identification so that the presence can run quickly and at a low cost. Attendance system helps employees and companies to run attendance faster and cheaper. The K Nearest Neighbor algorithm has a function as a classification algorithm in machine learning. The K value which is the highest accuracy by reaching 100% is 4 people with the determination of K equal to 3

Keywords


Presence System; Face Identification; Classification; KNN; Accuracy

Full Text:

PDF


Article Metrics

Abstract view : 447 times
PDF - 336 times

References

R. Wahyudi and O. Soesanto, “Rancang Bangun Aplikasi Pengenalan Pola Sidik Jari,” Kumpul. J. Ilmu Komput., 2015.

S. Nugroho and A. Harjoko, “Penerapan Jaringan Syaraf Tiruan Untuk Mendeteksi Posisi Wajah Manusia Pada Citra Digital,” Semin. Nas. Apl. Teknol. Inf., 2005.

Abdullah and K. R. Ku-Mahamud, “Ant system-based feature set partitioning algorithm for classifier ensemble construction,” Int. J. Soft Comput., 2016.

M. R. Alhaddad, “Manajemen Penilaian Kinerja Guru Palembang,” J. Kaji. Pendidik. Islam dan Stud. Islam, 2019.

M. M. Sofyan and K. Kamelia, “Analisis Pengaruh Pengembangan Sumber Daya Manusia Terhadap Kinerja Pegawai pada Sekretariat Badan Koordinasi Promosi dan Penanaman Modal Daerah (BKKPMD) Provinsi Jawa Barat,” J. RASI, 2021.

A. Mungki, A. Prima Putra, and F. Elly, “Pengembangan Aplikasi Munsell Soil Color Detection Chart Index Menggunakan Metode Support Vector Machine,” J. Inform. Polinema, 2018.

R. Szeliski, “Stereo Algorithms and Representations for Image-based Rendering,” 2013.

I. S. Faradisa and B. F. Budiono, “Implementasi Metode HUFFMAN Sebagai Teknik Kompresi Citra,” J. Elektro ELTEK, 2011.

A. Hendrawan, P. N. Andono, and S. Susanto, “ANALISA PENINGKATAN KUALITAS CITRA BAWAH AIR BERBASIS KOREKSI GAMMA dan HISTOGRAM EQUALIZATION,” J. Transform., 2016.

S. Firdaus and M. Adriana, “PENGEMBANGAN SISTEM DETEKSI KELELAHAN PADA PENGEMUDI MOBIL BERBASIS SINYAL ELECTROMYOGRAPHY (EMG),” Elem. J. Tek. MESIN, 2016.

S. Jaiswal, “Biometric: Case Study,” J. Glob. Res. Comput. Sci., 2011.

M. Yusuf, R. V. H. Ginardi, and A. S. Ahmadiyah, “Rancang Bangun Aplikasi Absensi Perkuliahan Mahasiswa dengan Pengenalan Wajah,” J. Tek. ITS, 2016.

A. Masruro, K. Kusrini, and E. Luthfi, “SISTEM PENUNJANG KEPUTUSAN PENENTUAN LOKASI WISATA MENGGUNAKAN K-MEANS CLUSTERING DAN TOPSIS,” Data Manaj. dan Teknol. Inf., 2014.

Ridho Ary Sumarno, “Aplikasi Klasifikasi Jenis – Jenis Buah Jeruk Menggunakan Metode K-Nearest Neighbor,” Artik. Skripsi Univ. Nusant. PGRI Kediri (Universitas Nusant. PGRI Kediri Fak. Tek. Prodi Tek. Inform., 2017.

S. Wiyono and T. Abidin, “IMPLEMENTATION OF K-NEAREST NEIGHBOUR (KNN) ALGORITHM TO PREDICT STUDENT’S PERFORMANCE,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., 2018.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Face Recognition using Webcam with K Nearest Neighbors Algorithm for Employee Presence

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Nurul Akbar Tanjung, Sanwani

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


The IJICS (International Journal of Informatics and Computer Science)
Published by STMIK Budi Darma.
Jl. Sisingamangaraja No.338 Simpang Limun, Medan, North Sumatera
Email: ijics.stmikbudidarma@gmail.com

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