ABSTRACT
The COVID-19 pandemic caused by the SARS-Cov2 virus has caused problems in various countries, including Indonesia. One of the provinces in Indonesia that has been affected by COVID-19 is Central Java. In order to prevent the spread of disease to a wider area, the government urges the public to wear masks, maintain distance and maintain good nutrition to increase body resistance. Goat's milk is one source of nutritional intake that is useful for increasing the body's resistance from respiratory diseases because it contains certain peptides, vitamin D and high calcium. With this, it is suspected that there will be an increase in demand of goat's milk during the COVID-19 pandemic in Central Java. This study aims to analyze the difference in demand of goat's milk between before and during the COVID-19 pandemic in Central Java. This study was conducted purposive method, with consideration, breeders who had a good record of the demand of goat's milk in the last 2 years and were willing to be respondents during the COVID-19 pandemic. The data taken was the number of collective requests of goat's milk before the COVID-19 pandemic (March 2019-February 2020) and during the COVID-19 pandemic (March 2020-February 2021). Two paired data from this study were analyzed by the Wilcoxon test to determine whether there was a difference or not. From the data collection, the average collective demand of goat's milk before the COVID-19 pandemic was 10,244 liters/month and during the COVID-19 pandemic was 22,065 liters/month, thus an increase of 115.39%. The results of the analysis using the Wilcoxon Test are known to have P-value = 0.002, so there is a high significant difference between the demand of goat's milk before and during the COVID-19 pandemic in Central Java. © 2023 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
The roselle plant (Hibiscus sabdariffa L.) is one of the abundant plants in South-East Asia, especially Indonesia. The roselle flower petals, a resourceful part of the roselle plant, contain a lot of antioxidants such as Protocatechuic Acid (PCA), Quercetin, Ascorbic Acid (AA), Cyanidin-3-O-Sambubioside (C3OS), Cyanidin-3-O-Glucoside (C3OG), and Tannic Acid (TA). The COVID-19 pandemic nowadays increases the hygiene lifestyle for the majority of people in the world. The repetitive usage of hand sanitizer has now become familiar in this state. So, it is interesting to develop natural-based hand sanitizer or hygiene products that are friendlier and has a less invasive effect on the skin. Roselle flower contains several types of antioxidants which have high reactive rates that can be used to alternate the use of alcohol as an active agent in hygiene products. Therefore, this research tried to conduct a theoretical study to understand the highest reactive roselle flower antioxidants by analyzing the reaction possibility of each antioxidant to the singlet oxygen (1O2) and triplet oxygen (3O2) with the help of Frontier Molecular Orbital (FMO) theory. One of the results shows that the PCA and AA have the highest reactive antioxidant rate to normalize1O2 with values of 1.22 eV and 1.86 eV. The C3OG and TA are also reactive antioxidants that bind the3O2 to prevent oxidation reaction with values of 3.61 eV and 3.50 eV respectively. This result supports the idea that the PCA and AA in roselle flower as antioxidants and natural acids can cause the inactivation of COVID-19 by breaking the protein membrane of the viral. This happens due to massive electron transfer and pH effect which dispose of the hydrogen bonds that preserve the viral structure. © 2022 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
Demand for touchless technology has grown with the surge of Covid-19 pandemic. Spontaneous gaze-based application is one of several promising technologies for touchless interaction. Despite of this potential, little attention has been paid to the performance of traditional eye movements classification methods on improving accuracy of gaze-based object selection. To handle this research gap, we proposed a novel workflow of spontaneous gaze-based object selection using 2D Correlation as similarity measure and Velocity Threshold Identification (I-VT) as a method for eye movements classification. We compared our method with Pearson Product-Moment Correlation (PPMC) as similarity measure and Dispersion Threshold Identification (I-DT) for eye movements classification. Our experimental results showed that the proposed method yielded object selection accuracy up to 95:62%+/-3:48%. In future, our proposed method can be implemented in the development of touchless interactive technologies that adhere to the World Health Organization guidelines, especially during the Covid-19 pandemic.