ABSTRACT
—The COVID-19 pandemic forced schools to change their offline learning model to online. Teachers can use many platforms for online learning, such as Google Classroom. This study aims to reveal the use of google classroom in online learning of Indonesian subjects at schools during the pandemic. A literature study is used in this research. Data is collected from various sources, such as journal articles, proceedings, books, and online news. The results of the analysis show that in learning Indonesian during a pandemic, Google Classroom is used by teachers as an online learning medium because it is easy for students to access. Using Google Classroom effectively increases student understanding and can increase student activity in learning. © 2023 ACADEMY PUBLICATION.
ABSTRACT
Hospital workers were at high risk for SARS-Cov-2 infection and the first population with authorized access to the three doses of vaccination against SARS-Cov-2 antigen. The study was aimed to compare SARS-Cov-2 antibody levels among hospital workers receiving the three doses of Covid-19 vaccines with a history of Covid-19 infection versus those without a history of infection. A cross sectional study was conducted at the Sulianti Saroso infectious Disease Hospital (SSiDH) in December 2021. The inclusion criteria were hospital workers in both subjects with and without previous Covid-19 infection and those who had received 3 doses of Covid-19 vaccines. Anti SARS-Cov-2 antibody levels measured by the Architect of SARS-Cov-2 igG ii Quant. There were 75 participants in the study, the median of anti SARS Cov-2 levels reported 8724.4 AU/mL (3396.8, 15773.2 AU/mL, interquartile range). They were divided into 2 groups according to the status of prior Covid-19 infection, hospital workers with and without previous of Covid-19 infection. There was no significance difference in antibody less than 25.000 AU/mL between hospital worker with and without previous Covid-19 infection (p=1,000). Meanwhile, the median of antibody levels was seen in the interval between the 3rd dose of vaccine within 1 month;2 to 3 months;4 to 5 months before the antibody measurement (14576.5 AU/mL;12407.4 AU/mL;5778.1 AU/mL, respectively). in this study, after three doses of Covid-19 vaccines, there was no significance difference in antibody levels of hospital worker with and without previous Covid-19 infection. Copyright © 2022 Oriental Scientific Publishing Company. All rights reserved.
ABSTRACT
Purpose: This research aims to select the best-fitting model(s) of equal risk contribution portfolios (ERC). ERC is a robust estimation in the absence of reasonable expectations about future returns. Design/methodology/approach: The portfolio consists of five environmental-friendly exchange-traded funds (ETFs). It applies equal risk optimization, beneficial when the assets are firmly linked, such as the ETFs. This paper operationalizes 20 covariance models in portfolio construction, and a portfolio with classic covariance is the benchmark to beat. To select the best-fitting model(s), the paper applies statistical inferences of the model confidence set. This research also constructs the newly-developed minimum connectedness optimization method and utilizes maximum drawdown as the primary evaluation tool. Findings: The outbreak of COVID-19 hugely impacts the portfolio drawdown. The results also show that the classic covariance is hard to beat, partly explained by estimation error and model misspecification. This paper suggests that equal risk contribution can benefit from copula-based covariance. It consistently and significantly outperforms the other models in various robustness tests. Practical implications: In the absence of substantial predictions about future returns and the existence of strongly linked assets, selecting appropriate portfolio components by risk contribution is a sound choice. Originality/value: This is the first paper to select the best-fitting model(s) of ERC portfolio during the COVID-19. © 2022, Emerald Publishing Limited.
ABSTRACT
Purpose: This paper aims to analyze the time-varying connectedness of gold-backed cryptocurrencies and gold. This study determines the volatility spillovers in these two asset classes and the performance of bivariate portfolios based on net pairwise spillovers. Design/methodology/approach: This research uses two Islamic and four conventional gold-backed cryptocurrencies and gold as variables. GJR-GARCH method under corrected DCC (cDCC) of Aielli (2013) evaluates the dynamic connectedness. Additionally, the spillovers are created using the dynamic connectedness of Diebold and Yilmaz (2012). A network-based spillover of Diebold and Yılmaz, (2014) is also made. A dynamic optimal weights strategy optimized with DCC-t-Copula determines bivariate portfolios’ performances. In general, there are 21 bivariate portfolios. Findings: The outbreak of COVID-19 increases the dynamic connectedness of gold and gold-backed cryptocurrencies, which indicates a contagion effect. The results show that gold is the net volatility receiver during the COVID-19 pandemic. Moreover, a portfolio composed of gold and gold-backed cryptocurrency provides high profitability performance but zero hedge effectiveness under optimal weights strategy. Practical implications: According to bivariate portfolios based on net pairwise spillovers, gold-backed cryptocurrencies' investors should not add gold to their portfolio during the pandemic because it is a net receiver of risk from the cryptocurrencies. Originality/value: To the best of the author’s knowledge, this is the first paper to create bivariate portfolios composed of gold-backed cryptocurrencies and their underlying asset using DCC-t-Copula. © 2021, Emerald Publishing Limited.