Prototipe Alat Pendeteksi Pengguna Masker Sebagai Upaya Pencegahan Covid-19
DOI:
https://doi.org/10.30595/techno.v24i1.11174Abstract
Upaya pencegahan penyebaran virus Covid-19 salah satunya dapat dilakukan  dengan cara  memakai masker, terutama diruang publik. Pengawasan terhadap sesorang memakai masker atau tidak memakai masker sangat membosankan terutama jika orang yang diawasi sangat banyak misalnya di terminal, bandara dan sebagainya. Oleh karena itu diperlukan terobosan alat untuk membantu pengawasan terhadap seseorang memakai masker atau tidak memakai masker untuk mengurangi beban kerja pengawas, dan alat dapat bekerja 24 jam tanpa lelah. Implementasi detektor masker pada penelitian ini menggunakan cara cepat dengan memanfaatkan google teachable machine. Hasil pengujian alat dapat mendeteksi seseorang memakai masker atau tidak memakai masker dengan tingkat kebenaran 100% baik pada obyek riil maupun obyek berupa foto atau video di komputer.
References
[1] X. Rizki, Saraswati Anindita ., Andree Kurniawan., 2020., Efficacy of Cloth Mask in Reducing COVID-19 Transmission: A Literature Review, Jurnal Kesehatan Masyarakat Nasional Kesmas, Vol 15 No 2.
[2] Joachim D Pleil, Jonathan D Beauchamp., et al., 2020, The scientific rationale for the use of simple masks or improvised facial coverings to trap exhaled aerosols and possibly reduce the breathborne spread of COVID-19, Vol 4 No.3, Journal of Breath Research.
[3] R. Davies, A., Thompson, K., Giri, K., Kafatos, G., Walker, J., & Bennett, A., 2013. Testing the Efficacy of Homemade Masks: Would They Protect in an Influenza Pandemic? Disaster Medicine and Public Health Preparedness, 7(4), 413-418
[4] D. Sari, Devi Pramita., Nabila Sholihah ‘Atiqoh., 2020., Hubungan Antara Pengetahuan Masyarakat Dengan Kepatuhan Penggunaan Masker Sebagai Upaya Pencegahan Penyakit COVID-19 Di Ngronggah, INFOKES, VOL 10 NO 1, FEBRUARI2020, ISSN : 2086 -2628.
[5] Lambacing, M. and Ferdiansyah, F. 2020. Rancang Bangun New Normal Covid-19 Masker Detektor Dengan Notifikasi Telegram Berbasis Internet Of Things. Dinamik. 25, 2 (Jul. 2020), 77-84. DOI: https://doi.org/10.35315/dinamik.v25i2.8070
[6] Dana H. Ballard; Christopher M. Brown ., 1982. Computer Vision. Prentice Hall.
[7] Pulli, Kari; Baksheev, Anatoly; et al., 2012., Realtime Computer Vision with OpenCV: Mobile computer-vision technology will soon become as ubiquitous as touch interfaces. ACM Queue Digital Library Journal.
[8] Bengio, Y.; Courville, A.; Vincent, P. 2013. Representation Learning: A Review and New Perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828.
[9] Ciresan, D.; Meier, U.; Schmidhuber, J., 2012. Multi-column deep neural networks for image classification. 2012 IEEE Conference on Computer Vision and Pattern Recognition. pp. 3642–3649.
[10] Chen, Yung-Yao; Lin, Yu-Hsiu; Kung, Chia-Ching; Chung, Ming-Han; Yen, I-Hsuan. 2019. "Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes" ., Sensors 19, no. 9: 2047.
[11] Matusugu, Masakazu; Katsuhiko Mori; Yusuke Mitari; Yuji Kaneda., 2003. "Subject independent facial expression recognition with robust face detection using a convolutional neural network". Jurnal Neural Networks, Volume 16, Issues 5–6, June–July 2003, Pages 555-559.
[12] G. Jignesh Chowdary, et al., 2020., Face Mask Detection using Transfer Learning of InceptionV3.,Cornell University, https://arxiv.org/abs/2009.08369v2
[13] Loey, Mohamed Loey, et al., 2020., A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic, Science Direct Measurement, Volume 167, 2021, 108288, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2020.108288. Published online 2020 Jul 28. doi: 10.1016/j.measurement.2020.108288
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) is licensed under a Creative Commons Attribution 4.0 International License.
