Differences in Muslim philanthropic behavior during the COVID-19 pandemic based on demographic factors

The COVID-19 pandemic that hit the country has caused a huge impact, especially on the economic sector. The approach taken by the government in dealing with the pandemic crisis by implementing a movement control order (MCO) have, to some extent, affected the source of income of the community. In order to survive, these underprivileged people are in need of financial assistance from the government, agencies and the kind-hearted people. Islam places great emphasis on welfare, especially in helping the needy with their daily needs. Therefore, this study aims to examine the level of philanthropic behavior of Muslims during the COVID-19 pandemic as well as to analyze the differences in Muslim philanthropies' behavior during the occurrence of this pandemic based on demographic factors, namely gender, age, education level, marital status, area of residence, household income and employment sector. To achieve this goal, a total of 424 respondents had answered a set of questionnaires distributed during the movement control order (MCO) period as a time limit via a simple sampling method. The results of the study found that five out of the seven demographic factors tested, namely age, level of education, area of residence, household income and employment sector showed significant differences in philanthropic behavior among the respondents. These findings also prove that demographic factors do also influence the decision-making process to donate among Muslims in Melaka. Therefore, all parties need to take a role in explaining and providing awareness on the importance of this philanthropic activity so that the burden borne by the community affected by the COVID-19 pandemic can be eased. © 2023 Author(s).

Relationship between philanthropic behaviour and the level of Muslim generosity during the COVID-19 pandemic

The Covid-19 pandemic has resulted in the layoff of 24 million people around the East Asia and Asia Pacific. This amount does not include those who are not working or are unpaid during the movement control order (MCO) period in Malaysia. Thus, many are economically affected to survive throughout this health crisis. In this regard, philanthropy plays a crucial role in the Muslims' economy as one of the instruments to aid those who have been affected. The objective of this study is to identify the relationship between internal factors (religious adherence, social sensitivity, appreciation and welfare satisfaction) and external factors (media advertising, government policy, environmental influences and visibility/prestige) that influence philanthropic behaviour and the level of Muslim generosity. This quantitative study utilises a survey method using a set of questionnaires that are structured and distributed to 424 respondents during the movement control order (MCO) period in the state of Melaka. The study findings show that out of the eight internal and external factors, all four internal factors and three external factors of philanthropic behaviour are significant in the level of Muslim generosity. Only one external factor which is the visibility and prestige (VP) is not significant in the level of Muslim generosity. This means during the Covid-19 outbreak, respondents gave donation with no intention of promoting themselves and institutions. Moreover, the practice of philanthropy is not aimed to spread one's influence on the society. © 2023 Author(s).

The use of teledentistry and Artificial Intelligence (AI) in dental and oral health services for the elderly in the era of the covid-19 pandemic: A systematic review

Objective: This paper aims to determine the use of teledentistry and AI in the elderly to maintain the health of their oral cavity and teeth during the COVID-19 pandemic. Methods: Technology in dentistry today is developing very rapidly, improving the quality of dental and oral health services. During the pandemic, the elderly has concerns about Covid-19 contamination when they have to see a dentist. Their situation has led to discussions and efforts to use teledentistry and Artificial intelligence to facilitate services and care for the elderly during the pandemic. Results: Teledentistry is used as a medium for consultation, diagnosis, referral system, treatment, and follow-up. While Artificial Intelligence (AI) has been used in diagnostic, patient data management, restoration, and CAD/CAM-based denture manufacture, detecting periodontal disease, and dental radiology. Conclusion: Teledentistry and AI can be a promising alternative in dental and oral health services to reduce anxiety and fear of contamination with Covid-19. The technologies make it easier for health workers, especially dentists, to maintain and improve the quality of life of the elderly during the pandemic. © 2022 JDMFS. Published by Faculty of Dentistry, Hasanuddin University. All rights reserved.

Analyzing the exchange rate USD/IDR under the impact of Covid-19 by using linear regression in Indonesia

The aim of this study are to build a statistical model, to analyze the time series trend of COVID-19 and exchange rate time series data, and to find the relation between COVID-19 as an independent and exchange as dependent variable. Linear regression as statistical model has been implemented to seek the relationship between COVID-19 and the exchange rate in Indonesia. The linear regression model were able to estimate COVID-19 case up to 88% with very small p-value. It means that the exchange rate USD/IDR has significant correlation with COVID-19. Thus, pandemic of COVID-19 had successfully given impact to economics factor in Indonesia. © 2022 Author(s).

Accuracy of Volatile Organic Compound (VOC) Detection in Exhaled Breath Compared to Reverse-transcriptase Polymerase Chain Reaction (RT-PCR) for Diagnosis of COVID-19: An Evidence-based Case Report

Background: Coronavirus disease 2019 (COVID-19) is a contagious infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The World Health Organization (WHO) declared this infection a global pandemic in 2020. In addition, various methods have been developed to diagnose COVID-19 rapidly and accurately to reverse transcription-polymerase chain re-action (RT-PCR) as a gold standard method. One of these methods is the detection of volatile organic compounds (VOC) in exhaled breath. Objectives: The aim was to collect and investigate studies on the accuracy of VOC detection as a diagnostic method for COVID-19. Methods: A literature search was performed in five electronic databases, including PubMed, Cochrane Library, ProQuest, EBSCO-host, and Scopus, along with hand searching. The search was conducted in the titles and s of articles using keywords and their equivalent terms, combined with the Boolean operators (OR and AND). The search results were then selected according to the inclusion and exclusion criteria and compatibility with the Population, Intervention, Control, and Outcomes (PICO) framework. Results: Based on the search results, two cross-sectional studies by Wintjens et al. and Ruszkiewicz et al. were selected, which were then critically appraised. Both studies showed good validity. Wintjens et al. reported 86% sensitivity and 54% specificity for their method, with a positive predictive value (PPV) and a negative predictive value (NPV) of 40% and 92%, respectively. Besides, Ruszkiewicz et al., who conducted a study in two different locations, reported 82.4% sensitivity and 75% specificity for their method in Edinburgh (UK), with PPV and NPV of 87.5% and 66.7%, respectively, while they reported 90% sensitivity and 80% specificity in Dortmund (Germany), with PPV and NPV of 45% and 97.8%, respectively. The accuracy of these three methods was 62%, 80%, and 82%, respectively. Conclusions: Detection of VOCs from exhaled breath can be a rapid, cost-effective, and simple method for diagnosing COVID-19. However, the accuracy of this method is still relatively low (62 -82%) and inconsistent;therefore, it is only recommended for screen-ing.

NEGATIVE CORRELATION BETWEEN OUTDOOR CYCLING PHYSICAL ACTIVITY AND DEPRESSION LEVELS DURING THE COVID-19 PANDEMIC AMONG MEMBERS OF MALANG CYCLING COMMUNITY

The purpose of the study is to analyze the relationship between the habit of outdoor cycling activities and the level of depression during the COVID-19 pandemic among the members of the bicycle community in Malang City. Materials and methods. This research is correlational, with a cross-sectional study approach. A total of 125 subjects from the bicycle community in Malang City voluntarily participated to become respondents in this study. The measurement of cycling physical activity habits was carried out using the International Physical Activity Questionnaire (IPAQ), while the measurement of the level of depression used the Hamilton Depression Rating Scale (HDRS). Measurements of physical activity habits and depression levels were performed at the same time. The data analysis used the Pearson product-moment model using statistical software package for social science (SPSS) version 17.0 with a set significance level (p ≤ 0.05). Results. The results showed that there was a negative correlation between the habit of outdoor cycling activities and the level of depression (r = –0.604;p ≤ 0.001) and showed a strong correlation between the two variables. Conclusions. Based on the results of the study, there is a negative correlation between the habit of outdoor cycling activities and the level of depression during the COVID-19 pandemic among the members of the bicycle community in Malang City. © 2022 Teoria ta Metodika Fizicnogo Vihovanna

Application of YouTube-Based Virtual Blended Learning as a Learning Media for Fundamental Movement Skills in Elementary Schools during the Covid Pandemic 19

Background. This study aimed to obtain an overview of learning outcomes using a virtual YouTube-based application as a medium for fundamental movement skills learning at the Elementary School. Methods. The method used in this study was classroom action research. The learning system created and implemented is a YouTube-based virtual learning system. The design used is a cycle model that includes planning, implementing, observing, and reflecting. The population used was a purposive sample of 32 students in 5th grade. The instrument used was in the form of field notes (Duration Recording), namely the use of virtual Blended Learning based on physical education YouTube videos for fundamental movement skills through observation with an average of 55% so that the target achievement was determined with an average of 80%. Results. Based on research in cycle I (Actions A, I, and W), 80.43%, because it has not exceeded the research target, it was continued to cycle II. Based on the results of the data analysis, the actions in the second cycle generated a perfect change (85.42%). This change can be seen after applying instructional media and explicit instructions that students can understand. Paired sample t-test shows the results of the value of 50.87 with p=0.000 <0.05, which means that there is an increase in students' fundamental movement skills. Conclusion. The fundamental movement skills learning using a virtual YouTube-based application is entirely meaningful in increasing the Learning Media for Sindang Sari 1 Elementary School students.

Digital thermometer innovation as a body temperature measuring tool for FKIP Mataram university employees during the covid-19 pandemic

The impact of the Covid-19 pandemic requires that every employee in a university maintains his health. One of the most important body parts to maintain during this pandemic is body temperature. The purpose of this study was to develop a non-contact digital thermometer to measure the body temperature of FKIP employees, Mataram University. The digital thermometer development method starts from literature studies, tool specifications, hardware design, software design and thermometer testing to measure employee body temperature in the morning and afternoon. The results of the digital thermometer test showed that the employee's body temperature in the morning with an average of 33.36 °C and in the afternoon with an average of 33.96 °C. So it can be concluded that the Mataram University FKIP employees who came to work did not experience Covid-19 symptoms. © 2022 Published under licence by IOP Publishing Ltd.

THE EFFECT OF VIRTUAL MEDIA-BASED OBSTACLE RUN TRAINING ON WOMAN FUTSAL PLAYER’S DRIBBLING ABILITY DURING COVID-19 PANDEMIC

The study purpose. This study aimed to observe the effect of virtual media-based obstacle run training on dribbling ability of women futsal players in the Women’s Futsal Student Activity Unit (UKM) during the Covid-19 pandemic by examining the effect of the treatment. Materials and methods. The research used a pre-experiment method using a quantitative descriptive approach with One Group Pretest-Posttest Design. A total of 30 students who participated in the Women’s Futsal UKM at the University of Suryakancana became the research population. These female futsal athletes are campus team amateur athletes below the professional level of the Indonesian Futsal League. Results. Based on research data, the average value before the obstacle run training treatment was 10.840 seconds and after the treatment was 9.600 seconds, which means that there was time reduction, or in other words, the woman futsal player’s dribbling ability increased. The result of the test showed that the value of the interval training results before and after being given was 0.859. Conclusions. It is suggested that further research explore the use of different kinds of media in improving the dribbling skills of futsal athletes during the Covid-19 pandemic. © Syamsul Taufik, M., Solahuddin, S., Pratama, R. R., Iskandar, T., & Ridlo, A. F., 2021.

Design of 2D LiDAR-based Indoor SLAM for Medical Robot Covid-19

Intelligent robot equipped with autonomous navigation system demand has been increased since Covid-19 pandemic to implement physical distancing among humans. To have autonomous navigation capability, the robot needs to be able to do mapping and use the map to navigate around the hospital. Mapping is performed in two unique places to simulate various hospital environments. Map results were then compared between the measurement on Rviz and the actual measured place. The system is proved accurate at 96% in the first place and 97% in the second place. © 2021 IEEE.

Applying the Islamic marketing ethics among small scale business Muslimpreneurs during Covid19 MCO: A comparison among types of social network system (SNS)

The outbreak of COVID-19 forced the Malaysian government to implement the Movement Control Order (MCO) in phases starting March 18, 2020. The implementation of the MCO has affected business continuity, especially among Muslimpreneurs involved in small-scale business. Restricting business hours and business movements to limited time periods and movements, entrepreneurs have turned to online and digital business methods specifically for marketing, supplying, and delivering goods. As a Muslim, Muslimpreneurs should not compromise with any unethical element in their entrepreneurial activities. Thus, business marketing and promotional activities conducted digitally and online should be in line with the Islamic law as well as the basic principles of ethics in Islamic business. This study used a content analysis approach to examine the implementation of Islamic marketing ethics in the sharing of business advertisements through Social Network System which is popular among Muslimpreneurs in Malaysia. For that purpose, a total of 45 samples of advertisements have been randomly studied from WhatsApp, Instagram and Facebook applications. This study found that over 90% of Muslimpreneurs have adhered to the basic principles of Islamic marketing ethics in their advertising material. At the same time, Muslimpreneurs are also found to prefer sharing quality ads and more on Facebook compared to WhatsApp and Telegram. © 2021 Author(s).

A comparative forecasting model of COVID-19 case in Indonesia

COVID-19 had been a disaster in Indonesia. Moreover, it is needed a study to analyze the trend of this case. The objectives of this study were (1) to propose the model for predicting COVID-19 using exponential smoothing, autoregressive integrated moving average (ARIMA), neural network, and fuzzy time series and (2) to compare the performance for each model by using RMSE as evaluation tool. In this study, the splitting data is implemented by 3:1 ratio on train and test data set. The results show that the neural network has the smallest error, 772.46 for RMSE. It means that neural network perform better than other forecasting model. Once, the characteristic data had big impact to building forecasting model whether in classical or modern model.