DETEKSI MASKER WAJAH MENGGUNAKAN DEEP TRANSFER LEARNING DAN AUGMENTASI GAMBAR
Abstract
Pandemi COVID-19 saat ini merupakan masalah kesehatan global. Menurut WHO, memakai masker wajah di depan umum adalah metode perlindungan yang efektif. Mengenakan masker merupakan salah satu gerakan 3M untuk pencegahan virus corona (selain mencuci tangan dan menjaga jarak). Bagaimana pun pengawasan pemakaian masker di ruang publik yang ramai bukanlah tugas yang mudah. Makalah ini mengusulkan penggunaan deep learning untuk mendeteksi orang yang memakai masker wajah dengan benar, memakai masker namun tidak benar dan yang tidak memakai masker. Kami menerapkan transfer learning dan augmentasi gambar, untuk meningkatkan kinerja model deep learning diusulkan secara keseluruhan. Penelitian ini menggunakan dataset CelebA untuk wajah tidak memakai masker dan dataset maskedface net untuk wajah yang bermasker dengan benar dan yang memakainya tapi tidak benar (seperti hanya menutupi mulutnya). Dengan menggunakan augmentasi gambar dan pembelajaran transfer, model yang dibangun mencapai akurasi 98,3% dan skor F1 98,7% pada dataset validasi. Hasil pengujian menunjukkan bahwa teknik augmentasi gambar dan transfer learning mampu meningkatkan akurasi model secara keseluruhan.
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DOI: https://doi.org/10.33387/jiko.v5i1.3591
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