Performance of Root-Mean-Square Propagation and Adaptive Gradient Optimization Algorithms on Covid-19 Pneumonia Classification

The SARS-CoV-2 coronavirus causes inflammation of the lungs, known as Covid-19 Pneumonia. Doctors or radiologists usually use lung images from X-rays to detect the condition of a person's lungs has Covid-19 Pneumonia or not. This research classifies x-ray images of the lungs using deep learning inti 3 categories, namely Covid-19 Pneumonia, Ordinary Pneumonia, and Normal. This method for classification uses the Convolutional Neural Network (CNN), which applies 22 layers containing 5 Convolutional Layers with dimension values 16, 32, 64, 128, and 256. This research tested the Root-Mean-Square Propagation (RMSprop) and Adaptive Gradient (Adagrad) optimization algorithms used to optimize the CNN performance model for Covid-19 Pneumonia classification. The experiment involved 3.900 lung images for the training process, 450 lung images for validation, and 225 lung images for testing. Based on the investigation, implementing the RMSprop optimizer produces an accuracy of 87.99%, a precision of 0.88, a recall of 0.86, and an f1 score of 0.87. Meanwhile, implementing the Adagrad optimizer produces an accuracy of 75.99%, a precision of 0.79, a recall of 0.72, and an f1 score of 0.75. These results provide essential information that the optimization algorithm of the RMSprop produces better performance than the Adagrad in classifying Covid-19 Pneumonia. © 2022 IEEE.

Creative Thinking Skills of Students in Determining Ideas for Development Biology Learning Media in the Light of Covid-19

Biology learning in the light of Covid-19 requires educators to have creative thinking skills in online classes. In particular, they are overcoming learning problems through the development of biology learning media. This study aims to determine student's creative thinking skills in determining ideas for development biology learning media in the light of Covid-19. There are four indicators of creative thinking skills described including fluency, flexibility, originality, and elaboration. This research is a descriptive study using a quantitative approach. The subjects in this study were 27 students of Biology Education in Semester IV who studied in the learning media course. The research has been carried out at FKIP Tanjungpura University for the 2020/2021 academic year. The research has been conducted in 8 meetings (half-semester). Quantitative data has been obtained from student answers working on structured project assignments and written tests which were analyzed in percentages, then converted into descriptive data. The results showed that the percentage of creative thinking skills was quite creative (51.85%). Fluency has the most significant percentage (81.30%), followed by elaboration (55.60%), originality (53.50%), and flexibility (45.50%). © 2022 American Institute of Physics Inc.. All rights reserved.