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

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