<p class="Abstract">Implementation of physical security such as recruitment of security officers, installation of CCTV, and restrictions on public access have become commonplace nowadays. Computer systems equipped with archival storage media must be properly maintained, including computer systems containing sensitive information that must be stored in a locked and secure place. This study applies a security system using facial recognition to determine who is authorized over the data in the computer system—using Haar Cascade as a face detector and LBPH as a match between faces that can access and those that are not on the list. On the other hand, if the person is unidentified, preventive measures will be performed. Based on the result, the proposed system using Raspberry Pi 4 is able to identify a face using Haar Cascade algorithm with an accuracy of 68% and average duration process of 0.392s, and able to recognize face using LBPH algorithm with accuracy between 50.74% to 100% and average duration process of 0.548s.<em></em></p>
To support autonomous vehicles that are currently often studied by various parties, the authors propose to make a system of predicting the distance of objects using monocular cameras on vehicles. Distance prediction uses four methods and the input parameter was obtained from images processed with MobileNets SSD. Calculations using linear regression are the simplest calculations among the four methods but have an error of 1% with a standard deviation of 1.65 meters. While using the first method, the average error value is 9% with a standard deviation of 0.43 meters. By using the second calculation, the average error resulted in 6% with a standard deviation of 0.35 meters. The experimental method had an average error of 1% with a standard deviation of 0.26 meters, so the experimental method was used.
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