Main Article Content

Abstract

At the beginning of 2020, Indonesia was shocked by the outbreak of a virus called Covid-19. One of the measures to prevent the spread of the epidemic is to wear a mask. In this research, a real-time mask detection system will be developed using eigenface and support vector machine (SVM). There are three main stages in this research, namely reading the image through the camera, calculating the eigenvalues, and classifying using SVM. The results of the classification consist of two classes, namely masked and unmasked. In general, if the eigenvalues ​​of the testing image are closer to the masked image, the output is masked and vice versa. The results of the research are quite good where the test is carried out through several test scenarios including considering lighting conditions, use of accessories, object distance from the camera, and so on. Most of the results obtained through system testing can distinguish masked and unmasked faces in real time.

Keywords

Computer Vision, Eigenface, Support vector machine Eigenface Support Vector Machine Visi Komputer

Article Details

Author Biographies

Nahya Nur, Universitas Sulawesi Barat

Informatika, Universitas Sulawesi Barat

Indra, Universitas Sulawesi Barat

Informatika,Universitas Sulawesi Barat

Farid Wajidi, Universitas Sulawesi Barat

Informatika, Universitas Sulawesi Barat

Iin Aisyah Khofifah, Universitas Sulawesi Barat

Informatika, Universitas Sulawesi Barat
How to Cite
Nur, N., Indra, I., Wajidi, F., & Aisyah Khofifah, I. . (2022). Sistem Deteksi Penggunaan Masker secara Real Time menggunakan Metode Eigenface dan Support Vector Machine. Jurnal Komputer Terapan, 8(2), 225–235. https://doi.org/10.35143/jkt.v8i2.5449

References

  1. A. Saputra, M. Ansori, and D. Widiatmoko, ‘rancang bangun alat pendeteksi suhu tubuh otomatis dengan image processing menggunakan metode backpropagation’, Jurnal Elkasista, vol. 1, May 2020.
  2. World Health Organization, ‘Panduan Interim: Anjuran mengenai penggunaan masker dalam konteks COVID-19’. Jun. 05, 2020. [Online]. Available: https://www.who.int/docs/default-source/searo/indonesia/covid19/anjuran-mengenai-penggunaan-masker-dalam-konteks-covid-19-june-20.pdf
  3. V. Wiley and T. Lucas, ‘Computer Vision and Image Processing: A Paper Review’, Int. J. Art. Intell. Research, vol. 2, no. 1, p. 22, Jun. 2018, doi: 10.29099/ijair.v2i1.42.
  4. A. Arfa, Farid wajidi, and Sugiarto Cokrowibowo, ‘Deteksi Wajah Dengan Metode Local Binary Pattern Histogram Pada OpenCV Menggunakan Pemrograman Pyhton’, jcis, vol. 2, no. 1, Sep. 2020, doi: 10.31605/jcis.v2i1.773.
  5. A. Wenda, ‘Support Vector Machine untuk Pengenalan Bentuk Manusia Menggunakan Kumpulan Fitur yang Dioptimalkan’, j. sains. teknologi., vol. 11, no. 1, pp. 77–84, 2022.
  6. R. Yulianti, I. G. P. S. Wijaya, and F. Bimantoro, ‘Pengenalan Pola Tulisan Tangan Suku Kata Aksara Sasak Menggunakan Metode Moment Invariant dan Support Vector Machine’, J-Cosine, vol. 3, no. 2, Dec. 2019, doi: 10.29303/jcosine.v3i2.181.
  7. L. Novamizanti, N. V. De Lima, and E. Susatio, ‘Sistem Pengenalan Wajah 3D Menggunakan ICP dan SVM’, JTIIK, vol. 6, no. 6, p. 601, Dec. 2019, doi: 10.25126/jtiik.2019661609.
  8. M. R. Muliawan, B. Irawan, and Y. Brianorman, ‘Implementasi Pengenalan Wajah dengan Metode Eigenface Pada Sistem Absensi’, Jurnal Coding, Sistem Komputer Untan, vol. 3, no. 1, pp. 41–50.
  9. W. M. Saputra, H. A. Wibawa, and N. Bahtiar, ‘Pengenalan Wajah Menggunakan Algoritma Eigenface dan Euclidean Distance’, Journal of Informatics and Technology, vol. 2, no. 1, pp. 102–110.
  10. Suroso and S. K. Ermaya, ‘Pengenalan Citra Wajah dengan Metode Eigen Face Menggunakan Matlab 7.11.0.548’, Jurnal IPSIKOM, vol. 6, no. 1, Jun. 2018.
  11. H. Nalatissifa, W. Gata, S. Diantika, and K. Nisa, ‘Perbandingan Kinerja Algoritma Klasifikasi Naive Bayes, Support Vector Machine (SVM), dan Random Forest untuk Prediksi Ketidakhadiran di Tempat Kerja’, JIUP, vol. 5, no. 4, p. 578, Dec. 2021, doi: 10.32493/informatika.v5i4.7575.
  12. A. C. Khotimah, ‘Comparison Naïve Bayes Classifier, K-Nearest Neighbor And Support Vector Machine In The Classification Of Individual On Twitter Account’, Jurnal Teknik Informatika, vol. 3, no. 3, pp. 673–680, Jun. 2022.
  13. R. A. Rizal, I. S. Girsang, and S. A. Prasetiyo, ‘Klasifikasi Wajah Menggunakan Support Vector Machine (SVM)’, Riset dan E-Jurnal Manajemen Informatika Komputer, vol. 3, no. 2, Apr. 2019.
  14. A. Thariq and R. Y. Bakti, ‘Sistem Deteksi Masker dengan Metode Haar Cascade pada Era New Normal COVID-19’, justin, vol. 9, no. 2, p. 241, Apr. 2021, doi: 10.26418/justin.v9i2.44309.
  15. F. L. Ahmad, A. Nugroho, and A. F. Suni, ‘Deteksi Pemakai Masker Menggunakan Metode Haar Cascade Sebagai Pencegahaan COVID 19’, Journal Education of Electrical and Electronic Engineering, vol. 10, no. 1, Jul. 2021, doi: https://doi.org/10.15294/eej.v10i1.47861.