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Nations, including India, expeditiously embraced telemedicine to provide primary healthcare due to the extensive disruptions from the pandemic caused by the novel coronavirus disease 2019 (COVID-19). This rapid integration was paramount, and the obstacles encountered during this critical period could offer valuable insights for developing and implementing future telemedicine endeavors aimed at fortifying primary healthcare services beyond the scope of COVID-19. Within the confines of this present review, we aim to elucidate the current applications of telemedicine in anesthesiology and perioperative care, delving into their potential impact, utilization, and conceivable challenges, particularly within the Indian context. [ABSTRACT FROM AUTHOR]

During the covid pandemic, many patients who were in intensive care or ventilation suffered from a fungal disease which was called mucormycosis. The fungal infection is mainly caused by common fungus in an atmosphere like fungus of species Rhizopusarrhizus, Lichtheimia, Mucor, Rhizomucor, etc. The infection is marked by simple symptoms like fever and nasal congestion to GIT bleeding and black lesions in moist body parts like the nose and eyes. Mucormycosis is fatal if not treated on time and with proper combination therapy. Sometimes in severe cases, surgery to remove the infected part is also advised. The present review is about the history and epidemiology and treatment strategies of mucormycosis. The article also highlights spread in patients with covid-19 and the underlying causes and management plan. [ABSTRACT FROM AUTHOR]

In today's time basically from ancient time India mostly uses ayurveda's culture and that bio-medical plants can be under a ayurveda to cure the disease by making medicine using herbs. Bio-medicinal plants is known to be medical herbs which having therapeutic properties and we use for various medicinal purpose. It can be classified into several types based on various usages and chemical components like Alkaloid rich plant, Terphenoid rich plants, Glycoside rich plant and many more. In the development of Bio-medical plants and herbs classifier we have used the Random Forest classifier to classify these Random Forest is a classifier utilizing many decision trees on different subsets of the input dataset and averages the results in order to improve the dataset's predictive accuracy. Also, QR codes have become increasingly popular in recent years, as they provide a quick and easy way to get information using a smartphone. There is an area to develop QR code particularly useful in identification and learning the information about medicinal plants and herbs. By generating QR code systems for plants and herbs, gardeners, horticulturists and other learners also can rapidly access information about a particular plant or herb, including its planting location, plant species plant origin, plant care instruction and plant identification etc. The use of QR codes has become more dominant during the COVID-19 pandemic as they provide a contactless way to get information and do transactions. QR codes are becoming gradually popular in the horticulture industry, providing a quick and suitable way for gardeners, horticulturists, and enthusiasts to access information about specific plants and herbs. This article discovers the development of a QR code system for various medicinal plants and herbs, its benefits, and potential applications in education and commercial plant sales. By using QR codes, individuals can expand their knowledge, promote sustainability, and enhance their overall experience with gardening. In this article the author introduces the QR code system for plants and herbs and how quickly it gives information about plants and herbs. the main use of QR code system is to store huge amounts of data in small areas so here time and space is completely utilized in an effective manner. [ABSTRACT FROM AUTHOR]

Because of increase in the prevalence of mental health problems in recent years, it's a need of the hour to explore the technological options for mental health monitoring especially after COVID 19 pandemic. Symptom profile of the psychiatric patients including lack of insight, reduced motivation, anhedonia, low self esteem may contribute for delay in seeking timely help along with other factors like inaccessible mental health care services, cost of the treatment (travel and medicine) and stigma. Wearable devices can help in remote patient monitoring, early identification and treatment, planning specific interventions, checking treatment adherence, and detecting early signs of relapse. Most research till now is done on anxiety, depression and stress. Few studies are also being done on panic disorders, post-traumatic stress disorders and bipolar disorders. Wearable devices for mental health monitoring utilize the physiological parameters like heart rate (variability), blood pressure, respiratory rate, cortisol level, skin conductivity, sleep quality, etc. Changes in these parameters are associated with symptoms of many psychiatric disorders or psychological issues. Type of wearables for mental health available in market include smart watch, actigraph, smart belt or ring, virtual reality headset, fitness tracker, etc. The real time data provided by these devices can help to plan new interventions, distant mental health monitoring, formulate new guidelines, research and behavioural monitoring. By integrating these wearables with various applications on mobile or laptop, quality of mental health assessment as well as quality of patients' life can be improved. Thus, wearble devices have a great potential for positive revolutionary change in the field of mental health if privacy and data safety precautions are properly practiced. [ABSTRACT FROM AUTHOR]

Preprints have played an unprecedented role in disseminating COVID‐19‐related science results to the public. The study aims to elucidate the role of preprints during the COVID‐19 public health emergency (2020–2023) through a quantitative analysis of journal papers. Among the 247,854 COVID‐19‐related papers published in PubMed, 12,152 were initially released as preprints and were eventually published in 1,380 journals. This number is more than five times the 246 journals to which submissions can be made directly from bioRxiv through the B2J program. Journals with higher impact factors and Normalized Eigenfactor scores tend to publish a larger number of preprint‐derived articles. The proportion of preprints among PubMed papers was 0.049, but this varies significantly by journal. In the top 30 journals, most exceed this proportion, indicating that these journals are preferred by authors for submitting their work. These findings highlight the growing acceptance and impact of preprints in the scientific community, particularly in high‐impact journals. [ABSTRACT FROM AUTHOR]

Health misinformation research has dramatically increased since the start of the COVID‐19 pandemic, although not all of this work has taken advantage of the rich theoretical and methodological background information science as a discipline has to contribute. This panel presentation will feature information scientists conducting health misinformation research from and in various settings, to showcase the value and range of information science approaches to health misinformation research. Each panelist will describe their work in the area of understanding and/or addressing health misinformation in institutions such as libraries and schools, health systems and interventions such as vaccination or public health promotion, or the general public in their online or offline information environments. Presentations will also highlight the ways researchers are applying information science theory, methods, and/or approaches to health misinformation topics, as well as lessons panelists have learned through this work. The panel will conclude with an interactive audience discussion that will center on the ways in which information science can help understand and address health misinformation challenges around the world. [ABSTRACT FROM AUTHOR]

Virtual storytime programs supported young children and families when in‐person library services were discontinued in response to the COVID‐19 pandemic in the United States. These virtual storytimes offered via videoconferencing systems allowed for the inclusion of some in‐person storytime elements such as the librarian read‐aloud, and children are the target audience of these picturebook read‐alouds. Children's nonverbal behavior symbolizes a powerful clue as to when they are engaged with the read‐aloud story. What is unclear is how a child nonverbally engages with the storytime readings. This study shows how human pose detection software, OpenPose, was instrumented with custom Python scripts to track and code a preschooler's nonverbal behavior during a virtual storytime read‐aloud. Results demonstrate considerable nonverbal attentiveness and engagement by this child during the read‐aloud. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has highlighted the importance of crisis research, particularly in the response phase. This research explores long duration crisis sensemaking of an Expert Advisory Group (EAG) during an emerging disease outbreak which has implications for the conduct of COVID‐19 public inquiries. The members of the Ontario SARS Scientific Advisory Committee (OSSAC) for the 2003 SARS outbreak in Canada, provide the context for this study. Among their duties, these experts were tasked to write directives (mandated protocols) that govern all aspects of hospital life, such as the protocol for transferring SARS patients. Data were collected in multiple forms, including: public inquiry reports, meeting minutes, newspaper articles, and interviews. Following a constructivist grounded theory strategy, several iterations of data collection and analysis were completed. The findings include a conceptual framework that depicts the sensemaking process and illuminates the relationship between retrospective (after an event has occurred) and prospective (future‐oriented) sensemaking. [ABSTRACT FROM AUTHOR]

Amidst the economic crisis caused by the Covid-19 pandemic, there is a projected growth and advancement anticipated in the global halal business. The economic growth potential of the halal industry has prompted numerous countries to engage in competitive efforts to develop and expand this sector. According to the 2022 Global Islamic Economic Indicator (GIE) report, Malaysia has attained the top position in the global halal business, but Indonesia, being home to the biggest Muslim population, has secured the fourth spot. Indonesian Vice President Ma'ruf Amin has set a goal for Indonesia to become as the leading global producer of halal products by the year 2024. In order to attain this objective, it is necessary for Indonesia to enhance its halal initiatives targeting female micro, small, and medium enterprises (MSMEs), particularly those operating within Islamic boarding schools. The objective of this study is to investigate the significance of kyai (Islamic religious leaders) and Islamic boarding schools in the development of the halal business specifically for female micro, small, and medium enterprises (MSMEs) in Indonesia. The selection of Paciran-Lamongan as a research site was based on the fact that its population resides in urban regions in close proximity to industrial zones. In contrast, Kangean Island was deemed less suitable due to its low infrastructure and restricted accessibility. The present study was carried out at two different locations: the Sunan Drajat Islamic Boarding School, situated in Banjarwati Village, Paciran Regency, and the Al-Hidayah Islamic Boarding School, located in Arjasa District, Kangean Island. The gathering of data in this study was conducted through a combination of several methods, including observation, focus group discussions (FGDs), and in-depth interviews. The findings of this study indicate that there are differences in the functions performed by kyai (Islamic religious leaders) and Islamic boarding schools in the regions of Paciran Regency and Kangean Island. Islamic boarding schools and kyai in Paciran play a crucial role in providing strong assistance for the halal certification process of women's micro, small, and medium enterprises (MSMEs). In contrast, the level of emphasis placed on halal certification attempts by kyai and Islamic boarding schools on Kangean Island tends to be limited. The level of coordination between women's micro, small, and medium enterprises (MSMEs) and the Government is currently inadequate, leading to a limited number of MSME products being certified as halal. [ABSTRACT FROM AUTHOR]

This paper aims to see how the impact of the covid pandemic on the transformation of digital culture in society in Ambon City is. The Covid pandemic has become an escalation of the transformation of digital culture and is the main marker for the creation of a conservative culture towards a digital culture. Although digital transformation has occurred, not all people in Ambon City are ready to face the transformation of digital culture. The lack of readiness of the mindset of the people of Ambon City is one of the triggers for individuals who are not ready to face the transformation of digital culture. The will to shift the mindset and explore the digital world has not grown well. The people of Ambon City do not yet have the urge to accept the existence of new technology and have the idea that technology is here to be studied in a disciplined and consistent manner. This research uses a literature study approach in elaborating the research topic. In the end, this study states that the impact of the covid pandemic has created a shift in conservative culture towards a digital culture. Thus, cultural changes in the midst of social life must be anticipated through a program to strengthen digital literacy. [ABSTRACT FROM AUTHOR]

Home Ownership loan (KPR) is one of the best products in every banking industry. That is because housing is part of basic needs. The Covid-19 pandemic that hit Indonesia in 2020 had impact on increasing credit fraud ratio. Therefore, a method is needed to overcome the risk of fraud on home ownership loans. The purpose of this study is to modeling of home ownership loan fraud risk with a binary response variable (faud and no fraud) so that binary logistic regression model is used and by using Multivariate Adaptive Regression Spline (MARS) that can accommodate the interactions between preditor's variables. Data collection was taken from data sample of PT Bank Mandiri Retail Credit Center Surabaya unit for the 2020-2022 period. The result of this study shows that significant relationship with the risk of KPR fraud are credit limit, collateral values, debtor salaries and employee status, while the credit period and interest rate have no significant on the risk of KPR fraud. Moreover, by using MARS approach gives better performance than binary logistic regression with an accuracy of 89% and sensitivity of 95.7%. Meanwhile the binary logistic regression approach gives an accuracy of 87% and sensitivity of 91%. [ABSTRACT FROM AUTHOR]

The flood of patients with respiratory problems during the coronavirus (COVID-19) pandemic can overwhelm the local healthcare systems, with the number of casualties exceeding local resources and capabilities in a short period. To temporarily replace the mechanical ventilator during mechanical ventilator shortages and to help clinicians triage patients, manual resuscitator devices can be used to deliver respirations to a patient requiring breathing support. The manual resuscitator which is based on a bag valve mask (BVM) was chosen as it is inexpensive, easy to use, widely available, and already has its safety features, however, it requires a medical professional to be present, and constantly applying compression to provide the patient with respirations. In this research, an automatic air bag-based mechanical ventilator was developed. This device provides automated compressions of a BVM repetitively. The treatment parameters supported in an automated air bag-based mechanical ventilator are tidal volume (VT), positive end-expiratory pressure (PEEP), the ratio of inspiratory and expiratory time, respiration rate (10 to 30 respiration/minute), and an adjustable fraction of inspired oxygen, FiO2. An oximeter was added to the ventilator system to measure the oxygenation level in the patient. Performance tests were conducted to evaluate the delivered tidal volume, respiration rate, I: E ratio, and FiO2 of the ventilator. The results were then compared with the commercial emergency ventilator. Using the statistical technique, it shows that a good agreement is obtained between the improved ventilator and the commercial ventilator. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has boosted the use of e-grocery significantly in recent years. However, older adults have been slow to adopt this new approach to grocery shopping, and this segment has received relatively less attention in literature. To fill this gap, this research investigates how trust and risk factors influence e-grocery adoption among older adults. The study surveyed 280 older adults using a quantitative survey questionnaire. The collected data was analyzed using regression analysis. The findings found the trust, performance risk and time risk play an important role in e-grocery use intention, while financial risk does not. The results enable businesses to design effective strategies to overcome the risks and barriers that older adults are most concerned with. Policymakers can also develop effective policies promoting e-grocery adoption among older adults, improving their quality of life and autonomy. [ABSTRACT FROM AUTHOR]

Unlike the influenza pandemic in the early twentieth century, scientists have rapidly identified the viral agents responsible for current SARS-CoV-2 pandemic. Moreover, scientists also have provided complete genome sequences of the virus shortly after the breakout in Wuhan, China in December 2019. Those achievement has been made possible not only because of the development of sequencing technology but also of the contribution of mathematics and computational biology in the field of bioinformatics. In the study of evolution phylogenetic tree approach give major drawback when reticulations such as lateral gene transfers, hybridization and recombination happened. And phylogenetic tree method could produce collection of trees because of incompatible phylogenetic signals. Thus, instead of the commonly used phylogenetic tree, one of the approaches in phylogenetic analysis in bioinformatics when the reticulations and incompatible signals were addressed is phylogenetic networks. In this article, we give literatures survey of the commonly used phylogenetic network method and literature survey of the use of phylogenetics networks method in the study of current SARS-CoV-2 pandemics and its evolution. We also provided phylogenetics networks analysis of 9 complete genome sequences consist of 3 SARS-CoV-2 isolates from human, 1 from bat, 4 pangolin hosts, and 1 coronavirus isolate from human host. The genome sequences were acquired from GenBank-NCBI database and similarity plot of the sequences were analyzed to detect recombination events. Phylogenetic networks were drawn by using Neighbor-Net and Median Networks algorithm. [ABSTRACT FROM AUTHOR]

The current global scenario is dominated by the Covid-19 pandemic, prompting various restrictions such as social and physical distancing in Indonesia to curb the virus's spread. Consequently, traditional banking activities have been limited, urging the society to shift towards digital banking methods. Amid this, mobile banking applications, including the BNI mobile banking app, have seen increased usage. This research seeks to assess the BNI mobile banking application's effectiveness and understand its impact on individual performance in banking activities during the Covid-19 pandemic. The evaluation utilizes the Delone & Mclean and Task Technology Fit (TTF) models. The research population comprises customers aged at least 17 years old who use BNI mobile banking, with 196 respondents forming the sample. Data was collected through online questionnaires, and SEM-PLS was employed for data analysis. The study findings indicate that user satisfaction and task technology fit are crucial variables influencing individual performance in banking activities, exhibiting the highest effect size and importance value among all variables. System quality and information quality positively contribute to user satisfaction, while technical and task characteristics positively influence task technology fit. Understanding the impact of mobile banking on individual performance during the Covid-19 pandemic is valuable for companies to enhance and assess their mobile banking applications, ensuring user retention and providing a positive impact on users. [ABSTRACT FROM AUTHOR]

The world of Indonesian cuisine is constantly evolving, both in terms of taste and presentation. The purpose of this research is to learn about the digital marketing survival strategies used by MSMEs Culinary. MSMEs Culinary attempted to survive in the midst of the increasingly erratic Covid 19 pandemic. The implementation methodology for this study is qualitative descriptive, with data collected through direct observation, interviews, library studies, and documentation. Using SWOT analysis, for example, can see strategies that can be used by using a variety of e-commerce digital marketing by creating online platforms such as websites, Facebook, Instagram, and market places (Shopee, Lazada, and Tokopedia), inviting food vloggers to conduct food reviews This survival strategy may allow MSMEs Culinary to stay in business and maintain sales. In this study it was also found that MSMEs need to diversify their strategy by changing marketing patterns from offline to online, so the steps taken to maintain their business are strengthening the brand by digitizing and creating accounts on social media and e-commerce, expanding the target market through e-commerce and improve product quality. [ABSTRACT FROM AUTHOR]

In this paper, we have presented a solution for monitoring environmental quality and keeping the air clean, called PAERO-1. It is an IoT-based robotic prototyping used for controlling the air quality based on state-of-the-art NodeMCU microcontroller but not limited to, sterilization, purifying, and measuring air quality in the context of Covid-19 pandemic. The correlated data such humidity, temperature, and volatile organic compound (VOC) are kept into the databank for further processing and decision making. The prototype has been tested with its functions working properly. In addition, this work present how PAERO-1 works with the hardware design and concept flow. Overall, this study is a detail of the IoT robot project to control air quality. [ABSTRACT FROM AUTHOR]

During the Covid-19 pandemic, almost all learning is done online through learning management system. All activities carried out in the learning management system are recorded in the event log. Only looking for the sequence of activities carried out by the learner is not an enough analysis of the event log. It is also necessary to see whether the activities carried out are effective. Analysis of event logs can be used to improve the quality of the learning process. The method used to get an effective event log activity is to develop a sequential pattern method, which is to find a sequence of activities that is low-cost while getting high utility. Low cost means that students use as little time as possible to complete an activity, while high utility means that students get maximum value learning outcomes. Learning outcomes can be in the form of quizzes or assignments. Measurement of the effectiveness of the pattern obtained is in terms of looking at the correlation between cost and utility of the pattern formed. This method is applied to analyse the event log obtained from the Moodle learning management system for one course. The experimental results show learning patterns in which they show effective patterns and can obtain patterns that can improve learning optimization. Searching for low-cost high-utility patterns in the event log of the learning management system is one effective way to improve learning performance. [ABSTRACT FROM AUTHOR]

The objective of this study is to assess the level of comprehension among Gen Z individuals regarding adherence to health protocols established by the government. In response to mitigating the spread of COVID-19, the government has mandated regulations such as handwashing, mask-wearing, social distancing, avoidance of crowds, restricted mobility, and vaccination (referred to as 6M). Given that Gen Z constitutes the largest demographic in Indonesia, they are a key demographic in ensuring compliance with these health protocols. This qualitative research involved 139 high school students and polytechnic students in Bandung. The findings indicate that Gen Z exhibits a high level of understanding regarding health protocols, and they actively strive to adhere to government regulations. The results suggest a positive inclination among Gen Z to comply with the prescribed health measures. [ABSTRACT FROM AUTHOR]

Although currently the residents of Bandung City who have been vaccinated have exceeded 70% and the number exceeds the target, but the COVID-19 pandemic is not over yet. COVID-19 will not disappear, and the disease will become endemic. Therefore, coexistence with the disease is a certainty. Reopening of schools, campuses, and offices under strict non-pharmacological measures (using masks, social distancing, routine sanitation, and reducing activities outside the home) is one way of coexisting with the disease. In term of making the places do not become new clusters of the spread of COVID-19, the opening strategy needs to be planned very carefully. This study proposes a mathematical model using a computational approach to estimate the maximum number of people allowed to be in a room with certain area for several hours in such a way that in the next one hundred days, if one person was infected at the start of the observation, no new people would be infected. Using a modified discrete SIR model and available data for the epidemiological parameters used this study showed a significant relationship between area of the room and duration with the number of people who will be in the room. The result is expected to provide consideration in formulating reopening strategy both during and after pandemic. [ABSTRACT FROM AUTHOR]

This study aims to determine the impact of the Covid 19 Pandemic on the stock markets of countries in Southeast Asia, including Indonesia, Malaysia, Thailand, Singapore, and Vietnam. This type of research is descriptive comparative. The data sampling technique used purposive sampling with the criteria for countries in Southeast Asia with stock exchanges. This study compares stock return index data between non-event and event periods (pre-event, event, short event, and long event) using the non-parametric Mann-Whitney t-test and paired sample independent t-test. It is concluded that there is a significant difference in the average return index between the non-event and pre-event periods, actual events, and long event periods. In addition, there is a significant difference in the accumulated return index between the non-event and pre-event periods, and there is a significant difference between the non-event and long event periods. [ABSTRACT FROM AUTHOR]

This study detects outliers of COVID-19 cases in the city of Bandung using the Mahalanobis distance. The existence of outliers is an early warning for the government to take action to suppress the spike in cases. These actions include the implementation of community activity restrictions and providing shelter for patients with mild and moderate symptoms. This outlier is also an early warning for hospitals to add health facilities, especially beds. The purpose of this study was to detect outliers of COVID-19 cases in the city of Bandung. This study also carried out monitoring to determine the sub-districts that had highest of outlier cases in the city of Bandung using the Pareto chart. Data on COVID-19 cases and bed utilization are very volatile, so the analysis uses the Moving Average smoothing. The results showed a spike in cases that occurred in June-August 2021. The government imposed the implementation of community activity restrictions so that cases could decrease in September 2021. Monitoring of beds provides information that outliers only occur in the use of isolation rooms B and A. Hospitals still need to add ICU room facilities if there is a very high spike in cases. This monitoring can be carried out on an updated basis so that when the Mahalanobis distance approaches the threshold, we can immediately take appropriate anticipatory actions. [ABSTRACT FROM AUTHOR]

The urban farming trend emerged during the government's lockdown. Urban agriculture has great potential to increase the value of nutritional consumption by providing healthy food for families, filling free time and some even use it as ecotherapy from fatigue working from home. In addition, urban farming can be a solution for many people who lost their jobs during the pandemic. This paper reviews the role of urban farming during the pandemic, especially when the lockdown occurred in the city of Makassar and the government's approach to encouraging community participation in implementing urban farming. Approximately 28 articles were selected after screening of 53 articles to ensure that they are related to the research. The selected articles are articles related to urban farming in Makassar City. The government encouraged urban farming programs prior to the pandemic, such as The Hallway Business Entity (Bulo) program, Sustainable Food Yards (P2L), Lorong Park Program and others. However, this has escaped the attention of the community. Limitations such as knowledge, area, relevant space, and opportunities to manage plantations hinder the participation of urban communities in this activity. During the COVID-19 pandemic, the good effects of urban farming gave urban communities awareness that food must be available so that many people participated in urban farming activities. Food security for urban communities must be maintained to anticipate a sudden crisis. Because there are so many problems such as global warming which is still a global problem and the threat of a crisis due to war, natural disasters. If urban food security can be maintained, social crises can also be anticipated beforehand. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic is a world crisis that has never been predicted before. This condition is a challenge for the world of education, including health education, especially in midwifery study programs. Education providers must develop a learning method that is adaptive to the conditions of the Covid-19 pandemic. This study aimed to examine the effectiveness of flipped classrooms for midwifery students on a particular subject. The subject matter explained contraceptive implants. The participant of this study were 60 female students of the 6th-semester level who took the Family Planning and Reproductive Health course. Quantitative research method with quasi-experimental pretest and posttest design. Each group had 30 students. Descriptive statistics and One-Way ANOVA were used to analyze the data. Even though the mean comparison (gain score and posttest) had not significantly different, the increased score between the pretest and posttest showed that the treatment group was better than controlled group. The flipped classroom supported by the contraceptive implant video enhances the students' understanding of the subject matter more effectively. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has had an impact on the restaurant business "Bebek Gazebo" located in the city of Makassar. This is related to reducing interaction between humans to reduce the number of increases in covid. This greatly affects the quality of service where there are these limitations. Restaurant service quality is one of the factors that can increase sales and attract consumers. The purpose of this study is to analysis the quality of service at the "Bebek Gazebo" restaurant. The consumers who were used as respondents were 100 people. Data analysis was carried out in this study namely simultaneous testing (F test) and the coefficient of determination (R-square test). The results of the F sig test 0.000 <0.05 of this study show that service quality (X) in this case X1 (reliability), X2 (responsiveness), X3 (assurance), X4 (empathy) and X5 (tangibles) have a positive effect on consumers' purchasing decisions (Y). The R-square test result is 0.576 which shows that 57% influences the purchase decision, and the remaining 43% is influenced by other factors. Restaurants need to improve the quality of service so as to be able to increase sales, make consumers loyal to the restaurant and attract new customers. Of course, all of this can help restaurants thrive and become the preferred destination for consumers to bring colleagues, colleagues and family. The Covid-19 pandemic is not an excuse to create inconvenience for consumers, with restrictions still being applied with ethics, morals and a good attitude. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been affecting the economic sector in terms of decreasing income from businesses, decreasing business production, shifting in society's shopping behaviour, and decreasing the amount of consumption of products. Indirectly, this disruption has transformed the pattern of fulfilling food needs. One of the business/industrial sectors that plays a role in fulfilling food needs is broiler chicken farming. Chickens are popular among Indonesians due to their high protein content. In addition, during the COVID-19 pandemic, everyone was encouraged to strengthen the body's immunity by consuming nutritious food. Before the pandemic, the demand for chicken meat in Indonesia increased every year and was always fulfilled. Production and demand for chicken meat experienced a very significant decrease when the pandemic entered Indonesia. This study aims to analyze the direct factors that influence the dynamics of broiler meat production before and during the COVID-19 pandemic in South Sulawesi. The research method used was a literature study with data sourced from 2021 livestock and animal health statistics documents. Data analysis was carried out using descriptive analysis techniques. Based on the data obtained, it is known that the dynamics of broiler meat production before and during the COVID-19 pandemic showed a negative growth rate of -3.29%. From 2017 and 2018, broiler meat production increased, but production has decreased significantly from 2018 to 2019. Then there was an increase of only 3.42% from 2019 to 2020. It increased by 3.41 percent between 2020 and 2021. This is the impact of the enactment of the Large-Scale Social Restrictions (LSSR) policy in South Sulawesi. Factors that directly influence the negative growth rate of broiler meat production trends are government policies in controlling the COVID-19 pandemic, access difficulties in distributing feed and broilers, a decline in livebird prices, reduction in the number of workers, and a reduction in the harvest intensity of broilers. [ABSTRACT FROM AUTHOR]

The achievement of food security at the regional or regional level does not guarantee the achievement of food security at the household level. When food availability is met, food security is not achieved. Food security will be achieved when access to food is also adequate and food absorption can take place properly. COVID-19 is a threat to global food security. Mandai District is one of the agricultural areas that has experienced an impact since the emergence of COVID-19 which affected the condition and food security of the community. This study was conducted to analyse the proportion of food consumption expenditure to total expenditure, the level of energy and protein consumption and the condition of food security of farmer households before and during the COVID-19 pandemic in Mandai District. This study method uses a descriptive-analytical method. Subjects of this study were 78 farming households in Mandai District which were affected by the COVID-19 pandemic. They were selected randomly. The results showed that the food security of farming households in Mandai District both before and during the COVID-19 pandemic was included in the category of food insecure households. This can be seen from the proportion of food expenditure which is still high (<60% of household expenditure), and the level of adequacy of energy and protein from food that is consumed less (≤80% of the requirement for adequacy of energy). [ABSTRACT FROM AUTHOR]

Agricultural extension services in Bulukumba Regency are carried out to increase agricultural production. However, since the outbreak of the Covid-19 pandemic in March 2020, the Bulukumba Regency government has prohibited its people from gathering in any form of activity. With this resistance, it becomes a problem for agricultural extension workers in carrying out their main duties and functions because communication as an essential means for extension workers to transfer innovations to farmers becomes disrupted or hampered. The purpose of this study is to describe the performance of agricultural extension services during the Covid-19 pandemic in Bulukumba Regency. The method used in this study is qualitative research using the survey method. The results of this study show that the performance of agricultural extension during the Covid-19 pandemic in Bulukumba Regency in coaching farmers / poktan continues as usual but has changed from the system and frequency of work. [ABSTRACT FROM AUTHOR]

The spread of COVID-19 is massive and greatly affects various aspects of life, ranging from health, and education, to the socio-economic community. In addition to providing drug therapy, optimal nutrition must be considered in managing COVID-19 patients. There are various ways to avoid this virus, one of which is by consuming vitamins, one of which is livestock products in the form of fresh milk. Public awareness of the importance of good nutrition during the pandemic has increased the demand for fresh milk. This type of research uses a literature study. This study aims to analyze the effect of the COVID-19 pandemic on the trend of fresh milk production in South Sulawesi. The analysis uses descriptive secondary data from the Central Statistics Agency and related literature. The results show a high demand for milk as a result of people being aware of the importance of consuming nutritious food to increase body immunity and reduce infection with the COVID-19 virus. Causing an increase in fresh milk production and the national cattle population. [ABSTRACT FROM AUTHOR]

Diverse technological advancements are being made during the current coronavirus pandemic as the initial step towards breaking the coronavirus chain. Spraying a disinfectant liquid regularly is one approach to breaking the COVID pandemic chain, particularly in public spaces. Automation-capable technology can be used to optimize the spraying of disinfection solutions. A disinfectant sprayer chamber is a technological invention as a result of this research. Using the ATemega328 microcontroller as an automatic machine to activate the sprayer pump in response to the identification of surrounding objects by an ultrasonic sensor, disinfection sprayers may be made to run automatically. The ultrasonic sensor's ability to communicate with the microcontroller is heavily dependent on the item's distance reading. The intelligent sprayer system is capable of turning on a 12 volt DC pump with a 5 amp voltage. The entranceway or corridor in the middle of the throng can be treated with this cutting-edge sprayer disinfection control system. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the impact of Polya model problem-solving and conventional problem-solving on students' Adversity Quotient (AQ) on Math subjects. This study was conducted during the student learning conditions during the Covid-19 pandemic. This was a quasi-experimental research with non-equivalent pre-test and post-test control groups. In Indonesia, 38 students from Ibrahimy Situbondo High School's class X took part in the study. Descriptive analysis approaches and inferential analysis with independent sample tests were employed to analyze the data. According to the descriptive analysis results obtained in the experimental class, students who utilized the issue solving Polya model had an average rise in grades of 3.39, whereas students in the control class who used conventional troubleshooting had an average gain in grades of 0.21. The paired test resulted in a sig value of pair 1 is 0.035<0.05 and on pair 2 produces a sig value of 0.480>0.05, which means pair 1 was a problem solving polya model that able to affect the increasing ability of AQ students. As for pair 2 was conventional problem solving which means by solving this problem can not affect the ability of AQ students. As the results of inferential analysis obtained significantly 0.569; it can be concluded that H0 was accepted and H1 was rejected because of the sig> value of α (0.569>0.05), then there was no difference in AQ which used polya model troubleshooting with conventional troubleshooting. [ABSTRACT FROM AUTHOR]

Core body temperature measurement is a key indicator of human health. However, its measurement, although very widely performed, is also often unreliable, especially through infra-red methods. This unreliability can lead to incorrect clinical diagnoses, treatment pathways and decisions about infection status, as, for example, during the recent Covid-19 pandemic. Here we give an outline of the issue and describe work undertaken by the CCT Task Group for Body Temperature Measurement to improve this situation. This has been through initiating a key comparison of body temperature calibrators, developing best practice for body temperature measurement by ear and forehead thermometers and thermal imaging and increasing engagement between metrology and clinical thermometer standards communities. [ABSTRACT FROM AUTHOR]

This semi-systematic review investigated the prevalence of long COVID and its impact on morbidity by measuring Years Lived with Disability (YLD) in India. The study involved comprehensive literature searches and rigorous screening of relevant studies. The results indicate an estimated 31.9% incidence of long COVID in COVID-19 infected patients in India. This incidence was then used to calculate an estimated 4,99,669 YLDs attributed to long COVID in the country. The study, despite its limitations, emphasizes need for better management strategies, healthcare planning, and continued research to address the persistent health effects of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Internet-of-Things (IoT) is collection of devices that works with Internet to connect various devices, to transmit data between devices, and to track and monitor devices. This has changed the lives by turning items "intelligent," enabling them to send information and carry out activities without human interaction. This is primarily an extension of the help provided by the Internet. IoT can automate home, office, or other unit, by connecting home appliances with the internet. IOT will be used for contact tracing during the COVID-19 pandemic. The most difficult obstacle for connected devices is various threats. This paper aims to presents detailed review on IoT systems, architecture, exploitable weak spots and summarizes various cyber security threats and solutions to those problems. [ABSTRACT FROM AUTHOR]

The recent COVID-19 pandemic has impacted all the nations worldwide in many ways. The pandemic has not only caused global health and economic crises but also affected the electricity distribution system. The impact of the pandemic on the electricity distribution system resulted from electricity consumption and demand behaviour that changed dramatically during the pandemic following the government regulation to regulate resident activities. This paper investigates the impact of the COVID-19 pandemic on the reliability of the electricity distribution system in Medan City. The reliability of the system is analysed based on three method: the system average interruption frequency index (SAIFI), the system average interruption duration index (SAIDI), and the customer average interruption index (CAIDI). The data applied in this study is collected from 2020 to 2022 and provided by PT. PLN (Persero), Medan, which is the national electricity company. The results showed that the average reliability index value for the system average interruption frequency index, the system average interruption duration index, and the customer average interruption index of the electricity distribution system Medan City from 2020-2022 is 8.2, 8.1, and 1,2, respectively. The results are compared to the IEEE Standard 1366-2003 and SPLN 68-2:1986 and show that the electricity distribution system of Medan City did not meet the reliability standard during the pandemic. These findings are expected to contribute to the decision and policymakers formulating future regulations and policies related to similar situations and avoiding future electricity reliability issues. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) involves the live presentation of digital objects within the real environment, offering supplementary details to tangible objects and facilitating interactive experiences. The benefits of AR in education, including heightened interest and motivation and enhanced learning enjoyment, render AR a captivating technology. Research on AR in education also becomes an intriguing topic to explore. In this study, we conducted bibliometric analysis to uncover trends and developments in AR research. We selected 568 articles from the Scopus database that met publication criteria, focusing on the field of education, in English, and in the form of articles rather than books, spanning from 2014 to 2023. The results showed that AR-related publications have been increasing since 2014, with significant growth since 2019, reaching its peak with a 100% increase in 2023. This rise was driven by the effects of the COVID-19 pandemic. The United States leads in the number of AR publications, followed by technologically advanced countries occupying the top 10 positions. Keywords most frequently used alongside AR include Virtual reality, education, e-learning, and technology. Future bibliometric research can delve deeper with broader databases and different time ranges to continue tracking developments in AR-related research trends. [ABSTRACT FROM AUTHOR]

Utilization of digital learning is spread massively after Covid-19 Pandemic. Students as learning purpose and are charged to master technology in the future must be adapted with learning paradigm change. Mathematics learning in elementary school need some media to help students understand with mathematics' abstract concepts. Several research state that digital media help elementary school students in knowledge and procedure in mathematics, but on other said, digital media causes mathematical anxiety for them. This paper elaborate how students are adapted with digital technology and what factor that support or hold them in learning these days. This research is Systematical Literature Review (SLR) with 111 and selected to 14 articles to review by using PRISMA step. The result is there are several factors that help and obstruct students to adapting with digital learning such as their relationship with teacher and classmate, facilities, parents support and curriculum, depends on the place that they come from. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic due to the SARS-CoV-2 virus is currently sweeping the entire world. This virus can spread easily and quickly, and one method to detect it is the RT-PCR method. One of the important steps of RT-PCR is the extraction of RNA. RNA extraction has been carried out using modified silica from Indonesian natural minerals: Kaolin Bangka Belitung and Bentonite from Pacitan. Before use, kaolin and bentonite were purified with different treatments to obtain extracted silica from kaolin and montmorillonite (MMT) fraction and Na-MMT from bentonite, which were subsequently made into silica coarse and then solidified into an extraction column (SPE column) and discs. Modified column (SPE column) and disc were then put into the vial of a commercial RNA extraction kit. Through FTIR, XRD, and SEM-EDX characterization, the formation of MMT, Na-MMT, purified kaolin, and extracted silica were confirmed. The SPE column and the disc that had been made were then evaluated based on the performance test prior to the RNA extraction process. Samples with positive RNA were tested to measure the CT values, RNA concentrations, and PCR processes. The results of this research showed only 2 silica matrices (SC-K and SC-MMT) were detected to have sufficient amount of RNA. Thus, further indication of the physical and chemical interaction between RNA and the modified silica coarse are crucial in order to understand the mechanism of RNA extraction. [ABSTRACT FROM AUTHOR]

Coronavirus Disease (COVID-19) is a new disease that first hit the world in 2020. This disease is thought to have originated in Wuhan, China [1]. WHO has designated COVID-19 as a pandemic which has successfully infected more than 190 countries in the world. DKI Jakarta is the capital city of Indonesia which is also one of the provinces with the highest number of positive confirmed cases of COVID-19 until the end of July 2020. This study aims to model the rate of COVID-19 cases in 15 sub-districts of DKI Jakarta with the highest intensity. The area of 15 sub-districts are chosen with the highest intensity to be the study area where more than 63.43 % of confirmed COVID-19 cases are in this area. The sub-districts are Gambir, Menteng, Sawah Besar, Kemayoran, Taman Sari, Senen, Tanah Abang, Johar Baru, Tambora, Grogol Petamburan, Cempaka Putih, Pademangan, Setia Budi, Matraman, and Palmerah. The rate of COVID-19 cases in this area is then analyzed using a GSTAR model. This model is one of the models in a stochastic time series that considers spatial component or location and time [2]. The binary weight matrix, uniform weight matrix, and distance weight matrix in this study were formed as a spatial dependency matrix among locations or called the W weight matrix. The results of Space Time Autocorrelation Function (STACF) and Space Time Partial Autocorrelation Function (STPACF) services for all spatial weighting matrices obtained the same model, that is GSTAR (3,1). Estimation of parameters of the GSTAR model (3,1) is carried out for each weighting matrix. The best GSTAR (3,1) model is based on a distance weighted matrix, with the smallest RMSE. [ABSTRACT FROM AUTHOR]

The increasing number of Covid-19 patients in the Surabaya, East Java area has affected the performance of the medical personnel who treat them. The medical personnel tire easily as the patient increases over time. Personal protective equipment is mandatory for medical personnel to use when working. However, it is not only a means of self-protection that is important, but the stamina of medical personnel is also important so that their health remains in prime condition. Apart from personal protective equipment, they also need tools to help treat Covid-19 patients. The concrete form of this tool is a food delivery robot for Covid-19 patients in supporting the patient's logistical needs. The method for designing this robot consists of the process of designing, manufacturing, assembly and testing the robot. This robot is designed to consist of a wireless remote communication unit, a camera / monitor unit, and an electrical unit. This robot is able to maintain a social distance between the medical center and patients and help the process of distributing food to Covid-19 patients who can be monitored with a monitor. [ABSTRACT FROM AUTHOR]

The global pandemic announced by the World Health Organization (WHO) in January 2020 has infected many people in various countries. The Covid-19 pandemic, caused by SARS CoV-2, is a disease that is difficult to diagnose because of its non-specific clinical symptoms. Some observed clinical symptoms include fever, cough, or shortness of breath that occurs approximately two days after exposure to the virus. RT-qPCR is a method that can be used to detect the SARS CoV-2 virus, with high sensitivity and specificity. However, this method has several disadvantages, including requiring special equipment, a long process, high costs, and the need for special expertise from operators and analysts in implementing the method. RT-LAMP is an alternative method that can detect the SARS CoV-2 virus faster with high sensitivity. The advantages of RT-LAMP compared to the RT-qPCR method are that it requires less equipment, a relatively shorter time, and a lower cost to detect the SARS CoV-2 virus. Our current study reported that the RT-LAMP machine showed an accuracy of 96.67 % in detecting the presence of the SARS CoV-2 virus. [ABSTRACT FROM AUTHOR]

Evaluating the risk for any investment is a challenging task. It requires the determination of various factors impacting the asset under consideration. The value-at-risk (VaR) measure has been widely accepted as an effective tool for risk analysis. This study provides a risk analysis of a stock portfolio from the sectors of Oil and gas, Consumer goods and retail, Engineering products and services, Finance and Banking, and Healthcare. The stocks were selected based on their market capitalization in the National Stock Exchange (NSE), India. VaR is computed using various techniques, such as the historical method, parametric method, Monte-Carlo method, GARCH and historical conditional VaR (CVaR). Additionally, the optimal weights of each stock in the portfolio have been determined. This work excluded the period from March 2020 to December 2020 from the VaR analysis, as it witnessed a significant variation in stock prices due to the COVID-19 wave. The estimated VaR indicated that the historical conditional VaR showed the fewest violations, while GARCH estimated the minimum VaR compared to the other techniques and thus a relatively higher percentage of violations during backtesting. This work highlights the dynamic nature of financial risk and underscores the need for adaptive risk management strategies that can evolve with the changing market conditions. [ABSTRACT FROM AUTHOR]

After Covid-19 pandemic, there has been no research that has modeled the number of plane passengers by considering the influence of seasonal effects. The purpose of the research is to predict domestic air passengers' traffic at Juanda Airport after the Covid-19 pandemic. The forecasting model used in this research is using the SARIMA-GLS-ANN hybrid model. SARIMA is used to capture linear data patterns while the GLS method excels in determining parameters. ANN excels in modeling data resulting from non-linear processes. The combination of linear approach in SARIMA, parameter estimation in GLS and nonlinear in ANN can be applied. A sample of 48 time series data from January 2019 to December 2022 was processed with the SARIMA-ANN method on SPSS 25, obtained valid data as many as 36 samples with 25 samples of training data (69.4%) and 11 samples of testing data (30.6%). The result of the difference in relative error in training data and testing data on SARIMA-ANN is 42.39%. Furthermore, data processing with the SARIMA-GLS-ANN method on SPSS 25 obtained valid data as many as 35 samples with training data as many as 23 samples (65.7%) and testing data as many as 12 samples (34.3%). The result of the relative error difference in training data and testing data on SARIMA-GLS-ANN is 4.29%. The SARIMA-GLS-ANN method is better at solving forecasting or predict domestic air passengers' traffic at Terminal I of Juanda Airport Surabaya. [ABSTRACT FROM AUTHOR]

In this paper novel making use of a CNN to forecast the spread of COVID-19 and comparing its accuracy with Logistic Regression is the main objective. Applying Logistic Regression and Convolutional Neural Networks to Regression are two groups used each with twenty samples to assess the accuracy of COVID-19 forecast. We used G power with an 80% pretest power to decide on the sample size. The CNN and LR algorithms were trained using data models that included both normal and COVID-19 chest X-rays. The accuracy of CNN is 98.5 % and LR has an accuracy of 77.7 % with a statistical significance of 0.496 (p>0.05). Compared to other methods, Convolutional Neural Networks use a to the Logistic Regression. [ABSTRACT FROM AUTHOR]

This study investigates a new method for COVID-19 outbreak prediction by means of an Artificial neural network (ANN) using convolutional layers (CNN). Compared to with an Adaptive boosting classifier. In this method, two groups are used. With the help of CNNs, one group and two more groups with Ada boost method employed a 20-person sample for each research to evaluate the precision of COVID-19 predictions. Applying G power and a pretest power of 80%, we determined the sample size. The CNN and Ada boost algorithms were trained using chest X-rays of both healthy and COVID-19 afflicted people. The results show that CNN achieved 98.5% accuracy and Ada boosted 79% accuracy, with a p-value of less than 0.05 indicating statistical significance. To review: Deep Learning Network algorithm has achieved better accuracy compared to the Ada boost classifier. [ABSTRACT FROM AUTHOR]

This research tests two neural network types—artificial neural networks and convolutional neural networks—to see whether one is better at predicting the spread of COVID-19. We evaluated the performance of Convolutional A Team Approach to COVID-19 Pandemic Forecasting with the Use of ML and CNNs using two sets of 20 samples. G power, which had an 80% pretest power, was used to compute the sample size. Data models were developed using Chest X-rays from healthy individuals and COVID-19 patients were used in conjunction with artificial neural network (ANN) and convolutional neural network (CNN) methods. The results show that CNN has a 98.5% accuracy rate and ANN 95.33% accuracy rate, with a p-value less than 0.05 indicating statistical significance. When compared with the Artificial Neural Network method, the Convolutional Neural Network method yields better results in terms of accuracy. [ABSTRACT FROM AUTHOR]

The major objective of the researchers doing this study was to determine the effects of the Novel Coronavirus pandemic on the sleeping patterns of persons residing in both rural and urban areas. It was found that around 454 answers were genuine. The dietary influence on urban and rural people of Kanchipuram and Chennai was examined in this research using SPSS software and the chi-square test. To determine the sample size, an 80% G-power, a 0.05 α-value, and a 95% confidence interval were used. A significant portion of the participants (78.36% of the total, p<0.001) reported that stress and their past sleeping habits either disrupted or worsened their sleep patterns. A decrease in nighttime sleep duration and an increase in daytime naps were noticeable changes between the pre- and post-lockdown periods. Health care practitioners were untouched by these impacts, even though they were obvious across all sectors. Even so, they affected the majority of persons in the labour force. The night's sleep was dull for everyone. There was a correlation between the duration of sleep and symptoms of depression. There is a new COVID-19 lockdown that is associated with people's sleeping patterns, including their quantity and time of sleep every night. Despite these changes being associated with higher incidence of emotional symptoms, innovative cross-sectional data analysis makes it difficult to determine whether sleep deprivation causes psychological discomfort or if the pain causes sleep deprivation. [ABSTRACT FROM AUTHOR]

In the end, we want to use a database of chest X-rays together with some deep learning-based machine learning to discover novel COVID-19 predictions. With the use of computer-aided detection, chest X-rays may reach this level of precision. Nevertheless, there has been little focus on the latest CAD results for detecting new corona virus predictions and concurrent pneumonia on CXRs. The Kaggle library accurately detects the deletion of COVID-19. We chose 30 examples out of a collection of 2,000 chest X-rays. Alexnet and Googlenet are the names of the two groupings. According to the results, Alex net outperformed Google net with an accuracy of 96.18%. Alex net performs better than Google net over the long term. Two approaches used in the independent sample t-test meet the statistical criteria with a 90% confidence level and a p-value of 0.001 (p<0.05). According to the results of the research, the main goal of the project is to develop and improve algorithms for predicting the spread of COVID-19. Alexnet outperforms Google net, according to the results. [ABSTRACT FROM AUTHOR]

In contrast to Yolo-v3 and the New Yolo-v4, the research suggested uses a Convolutional Neural Network built on an actual-time entity identification technique to identify facial masking. We present the Yolo-V3 method and compare it to the new Yolo-V4 algorithm. Utilizing G power (80%), the sampling number was determined to be 40, meaning 20 for each group. In terms of statistical significance, the two groups vary by 0.00041 (p<0.05). By comparison, the Yolo-v3 achieved a mean precision rating of 91.14 and the Novel Yolo-v4 had a mean precision of 96.37, as shown in the simulation results. By offering preventative strategies, the Yolo-V4 system has become better at containing the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

In Malaysia, the movement control order (MCO) was imposed since 18th March, 2020 to stop the spread of COVID-19 and all higher education institutions are physically closed and all teaching and learning activities are converted to online activities. After more than 90% of the public has gotten vaccination and when the pandemic is transitioned to the COVID-19 endemic, hybrid and full physical teaching and learning activities are coming back. The investigation of students' learning experiences are valuable as part of student-centric education paradigm. The software tools, online learning platforms and social media resources have become an integrated part of the learning process of undergraduate students. Therefore, it is essential to investigate their roles during COVID-19 pandemic in Malaysia by the undergraduates. A survey on the preferences from the software tools, online learning platforms and social media resources aspects by undergraduates of mathematical and IT disciplines was conducted in a private higher institute in Malaysia. The data analysis revealed that online mathematical and free programming tools are the most widely used software, Microsoft Teams as the most effective online teaching and learning platform and YouTube is the most effective social media resources. [ABSTRACT FROM AUTHOR]