No abstract

Indonesia ranks 23rd as the most COVID-19 confirmed cases in the world. DKI Jakarta and East Java provinces have the highest cases in Indonesia. However, data on the transmission of COVID-19 in both provinces were not further analyzed regarding vulnerability between genders. This research attempted to compare the differences in the gender distribution of COVID-19 cases by analyzing data from COVID-19 DKI Jakarta and East Java Task Force Information Center and various biological, medical, and socio-cultural studies to understand risk of women being exposed to COVID-19. The results of this research revealed that both provinces had a higher number of confirmed patients under surveillance (PDP), people under surveillance (ODP), and death cases in men than that of women. In DKI Jakarta, the number of recovered cases in men was higher than that of women, but in East Java it was not significantly different. Based on literature reviews, women were more resilience in manifestations of COVID-19 severity than that of men due to differences in ACE2 gene distribution and expression, hormones regulations, immune responses, comorbidities, and ages. However, data from socio-cultural literature reviews in both provinces showed women were vulnerable to be exposed to COVID-19 since many women performed as health workers, office workers, market traders, public transportation users, and did religious activities. Besides, women were vulnerable due to mental health condition, such as depression, anxiety, and special medical condition (e.g. being exposed to or infected with COVID-19 during pregnancy).

Various studies regarding to Steady State Visual Evoked Potentials (SSVEP) based Brain Computer Interface (BCI) system with Electroencephalogram (EEG) signal has developed as BCI implementation on directional control, however lackness found on those studies which are long time on classification duration, to many electrode channels used and the electrode channels located on special area. This study we developed the SSVEP based BCI system with one second classification duration, four active channels used and electrode channels located based on The International 10-20 System. Stimulus used are red colored object with 11 Hz frequency rate represents as left directional control class, blue colored object with 13 Hz frequency rate represents as right directional control class and white colored background represents as relax class. Filter bank with eight frequency range (11 Hz, 22 Hz, 33 Hz, 13 Hz, 26 Hz, 39 Hz, 12-29 Hz dan 30-50 Hz) followed by Root Mean Square (RMS) used as  feature extraction for every second of data. Artificial Neural Network (ANN) classification and 5-Fold Cross Validation are used to knowing the performance of the developed system. Developed BCI system resulted accuracy 78,20% with True Positive Rate (TPR) 86,00% and False Discovery Rate (FDR) 23,21%.