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All Journal Jurnal ICT : Information Communication & Technology
Fajar Nazmi Fadillah
STMIK AMIKBANDUNG
Computer Science & IT

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Sistem Deteksi Penggunaan Masker pada Pengunjung STMIK “AMIKBANDUNG” menggunakan Algoritma Convolutional Neural Network (CNN) Khoirida Aelani; Fajar Nazmi Fadillah
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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Abstract

The STMIK "AMIKBANDUNG" visitor data monitoring system currently still does not have input that can detect whether a visitor is wearing a mask or not. This has resulted in the campus not having data to see whether the campus environment has implemented health protocols to avoid COVID-19 to the fullest. Manual data collection will take time, while the system currently used is web-based with no support or documentation using a machine learning-based mask detection module. Machine learning is a branch of artificial intelligence which includes building systems based on data. In this study, machine learning with the Convolutional Neural Network algorithm will be applied to develop mask detection. The end result of this research is a mask detection system that is more effective and efficient from a programmatic point of view because it uses the Python language, is supported by an interactive interface and user experience, and is accompanied by documentation so that the program can be developed further. By leveraging artificial intelligence, campuses can make decisions more easily with the support of statistics showing the number of violations through the website interface
Co-Authors Khoirida Aelani