ABSTRACT
In 2022, the COVID-19 pandemic is still occurring. One of the optimal prevention efforts is to wear a mask properly. Several previous studies have classified the use of masks incorrectly. However, the accuracy resulting from the classification process is not optimal. This research aims to use the transfer learning method to achieve optimal accuracy. In this research, we used three classes, namely without a mask, incorrect mask, and with a mask. The use of these three classes is expected to be more detailed in detecting violations of the use of masks on the face. The classification method used in this research uses transfer learning as feature extraction and Global Average Pooling and Dense layers as classification layers. The transfer learning models used in this research are MobileNetV2, InceptionV3, and DenseNet201. We evaluate the three models' accuracy and processing time when using video data. The experimental results show that the DenseNet201 model achieves an accuracy of 93%, but the processing time per video frame is 0.291 s. In contrast to the MobileNetV2 model, which produces an accuracy of 89% and the processing speed of each video frame is 0.106 s. This result is inversely proportional to accuracy and speed. The DenseNet201 model produces high accuracy but slow processing time, while the MobileNetV2 model is less accurate but has faster processing. This research can be applied in the crowd center to monitor health protocols in the use of masks in the hope of inhibiting the transmission of the COVID-19 virus. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Advocates are one of the elements of law enforcement that are crucially needed by justice seekers;hence, a good legal education is needed. Then, how is the advocate education process during the COVID-19 pandemic? This study will reveal the perspectives of prospective advocates in participating in the Special Advocate Profession Education (PKPA) during a pandemic about how their motivations, reasons, and experiences continue to follow the education process under the shadow of the coronavirus that still exists. This qualitative research was conducted on 40 prospective advocates who participated in the 12th PKPA Batch in 2021. The data were obtained by conducting in-depth interviews with each PKPA participant and recording them. Furthermore, audio analysis was conducted to maintain the validity of the data. The findings showed that a strong passion for becoming an advocate is their ambition, and the legality of PKPA organizers and the application of health protocols are the reasons for prospective advocates to continue their education during a pandemic. Another finding was the experience of PKPA participants who considered that new adaptations were needed, and feelings of limited and technical obstacles were barriers that had to be further corrected in the implementation of advocate education. The implications of this research are to provide constructive advice for advocate education providers in implementing PKPA well during the pandemic and provide more attractiveness to prospective participants to participate in PKPA comfortably and safely. © 2022 Hamsir et al. This is an open access article licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.
ABSTRACT
Existing elevators use a wide variety of methods in their systems to provide a direct response to the input received by first checking the inputs to operate. This response is related to the movement of the elevator itself. The research was conducted to minimize the movement of the elevator. In addition, as a form of effort to reduce the spread of Covid 19, the touchless button is introduced to the elevator operating system. The provision of the fuzzy logic method will make the elevator system manage the input given to determine priorities in the elevator movement. There are several input variables in the fuzzy method: position, distance, direction, and elevator capacity. Fuzzy logic will manage these variables, which are then obtained in the form of elevator movement priority. PLC used in this study is PLC Outseal Mega V1.1 as a controller on the elevator. The input uses a proximity infrared sensor so that it can provide input without touch. The use of functions on the PLC such as comparators, timers, and counters can realize an elevator system based on fuzzy logic calculations. The output used is a relay that will operate the DC motor. The proposed method realizes an innovative elevator operating system to stop the spread of covid 19. © 2021 IEEE.