Search

Nowadays, there are numerous and wide variety of online learning platforms (OLP) available for students and educators. In order to make the online learning process run smoothly, educators need to be smart in choosing a good medium to use. Many factors should be considered concurrently during decision-making processes. As a result, Multi Criteria Decision-Making (MCDM) method, which seeks to pick the best option from a set of choices, can help decision makers in making suitable and unambiguous judgments in difficult situations. To evaluate such difficulties, this paper combines neutrosophic set with the Best-Worst Method (BWM) approach. The neutrosophic set is important in solving indeterminacy problems and it is more suitable to solve real-world decision-making problems. Besides, in the MCDM problem, similarity measures may be used to describe how different alternatives vary and are similar to one another. However, it appears that the existing similarity measures seem to have a few major weaknesses and inherent problems, such as producing unreasonable results in some cases. Therefore, to cater such problems, this paper introduced a novel single-valued neutrosophic best-worst method, SVN-BWM approach with improved similarity measures of the single-valued neutrosophic set (SVNS) model into a case study of selecting the best online learning platforms based on educators' preferences. The data are collected from six decision makers (DM) among Mathematics lecturers of Universiti Teknologi MARA (UiTM) Shah Alam. From the findings, it is found that Google Meet is the most preferred online learning platform. [ABSTRACT FROM AUTHOR]

With the strike of the covid-19 outbreak end of 2019, the styles of teaching and learning at the higher institutions all over the world were forced to online platforms. This paper discusses the difference level of understandings in solving the hypothesis testing problems for four different groups of non-statistical students at the Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia. Methodology: This observational study involved 102 students comprises of four groups (A, B, C and D) from the Faculty of Hotel and Tourism Management, UiTM Shah Alam who enrolled for Statistics for Business and Social Sciences during academic semester March – August 2022. The scores of test which consist of six problems related to hypothesis testing for one population mean, the difference of two-population means, dependent (paired) samples, Analysis of Variance (ANOVA), test of association and Regression were analyzed using the Welch's ANOVA test. Result: The findings clearly show that whilst the students from different groups received the same method of lectures and guidance from the same lecturer, the scores for test were significantly different between two groups; between A and C and between C and D. The scores for Question 1 – Regression analysis and Question 3 – Analysis of Variance (ANOVA) questions were significantly different between group C and D and the scores for Question 1 only between group B and C. In addition, this paper innovatively identifies prevalent statistical errors committed by students, contributing to enhanced understanding and improved learning in statistics. [ABSTRACT FROM AUTHOR]

In a pandemic outbreak such as COVID-19, that spreads widely around the world requires in depth research to predict the pattern of its spread and strategies to reduce the number of spreads. Predictive control is a mathematical approach to control systems where a model is used to make predictions about the future behavior of a system, and these predictions are then used to determine the control actions that should be taken. Based on these predictions, control measures such as lockdowns and social distancing could be optimized to reduce the spread of the virus and minimize its impact. A dynamic model is needed for quick and precise handling decisions. Mathematical models Epidemiology can be used in various fields, the implementation of which is COVID-19. The presentation of a dynamical system can use the basic compartment model, in which critical 퐶 and death 풟 states are considered, addressing more possibilities of mutual transitions between compartment states. 풮ℰℐℛ풞풟 estimates and forecasts the COVID-19 spread under uncertainties and constraints. This paper focuses on This paper focuses on fit and predict the 풮ℰℐℛ풞풟 model with time dependent basic reproduction numbers and health resource-dependent death rates to real COVID-19 data in Indonesia. Data have been collected for a specific period of time, the best-fitting parameters have been obtained, and the changes in the basic reproduction number over time have been estimated. The presented model has included the transition probability of the infected state to the critical state and the transition probability of the critical state to the death state, based on different age groups, so that the number of hospital beds has also been cooperative in computing the compartment states. Using the best-fitting parameters of the 풮ℰℐℛ풞풟 model, the development of the compartment states in the near future was estimated. The simulation result shows that the obtained parameters of the 풮ℰℐℛ풞풟 model were reasonably satisfying where the simulated states from the model could fit the real data with a small degree of error so that it can be used to predict the path of further deployment. [ABSTRACT FROM AUTHOR]

In this paper, we describe the dynamics of the spread of the COVID-19 disease. In this paper, a mathematical model of the problem is rewritten. Mathematical models can be used to find strategies to prevent the Coronavirus disease spread. A Susceptible-Exposed-Infected-Recovered (SEIR) mathematical model in the spread of COVID-19 disease is solved using fourth and fifth-order Runge-Kutta methods. The simulation results of the two methods show the same pattern of solution behavior as the results of the reference solution obtained using the ODE45 algorithm in the MATLAB software. Theoretically, the accuracy of the fourth-order Runge-Kutta method is not better than that of the fifth-order Runge-Kutta method. We show the correctness of this theory through simulations in this paper by solving the SEIR mathematical model for the COVID-19 disease. [ABSTRACT FROM AUTHOR]

This concept paper explores the challenges faced by employees from various industries as the world faces the COVID-19 pandemic at this point. The current situation finds that employees cannot go out to work face to face or are not allowed to come to the office physically as usual as a result of this COVID-19 pandemic outbreak. Furthermore, all citizens from almost all countries are involved in the implementation of the movement control order (MCO). However, jobs that involve day-to-day operations in the organisation still need to carry out their activities as usual for the sake of the survival of their respective organisations. Thus, there are various online platforms that are used to enable activities in the organisation to continue in the interest of stakeholders. To continue daily work activities there are several online platforms that are often used as communication media in organisations such as 'Google Meet', 'Google Classroom', 'Zoom', 'Webex', 'Microsoft Team' and 'Skype'. When the COVID-19 pandemic situation was announced to have subsided, there were organisations that adopted hybrid methods where online and face-to-face communication media were practiced for the purpose of discussions and meetings. This concept paper aims to identify the challenges faced by employees throughout working from home (WFH) when faced with this COVID-19 pandemic. Researchers have proposed three (3) recommendations in facing employee challenges throughout WFH with reference to Sociotechnical Systems Theory (STS) and Motivation-Hygiene Theory based on reference highlights of papers reviewed from 15 journals in previous studies. The results of this study can contribute to knowledge and in addition to the highlights of the work for this topic, especially to employers and employees who practice the concept of WFH. [ABSTRACT FROM AUTHOR]

For more than a year and a half, educators and students have been navigating the stormy seas of remote teaching-learning. After months of the coronavirus epidemic and countless research on its impacts on university teaching and learning, the repercussions of this unparalleled state of affairs are only partially known. This paper adds to the current research on how university teachers have dealt with it in an effort to understand the impacts on teaching the course of "design studio" that has never been taught online before. However, many are returning to in-person classes or planning to use a blended teaching approach. As a result, the second purpose of this study is to learn more about how teachers plan to teach in the future, which is an innovative topic that has piqued our attention. Six professors agreed to let us observe their design studio classes for the total period of 8 months spread over three semesters from 2020 and 2021. The majority of students had favorable experiences with online teaching and examinations, and most would welcome this format in the future, according to an analysis of these programs. The same cannot be said for teachers, who see this method of instruction as time-consuming and demanding. Simultaneously, this paper aims to highlight the advantages of remote teaching-learning models in teaching design studios, suiting students' educational needs, and aiding in their professional growth as architects. The research stems from the hypothesis that the pandemic will have a long-term impact on lesson planning, and opens a fresh discussion about multi-mode educational implications that learners, teachers, and other education actors should consider in the next phase of post-COVID-19 era before deciding on going back to the pre-COVID-19 pandemic classroom teaching-learning. [ABSTRACT FROM AUTHOR]

Promotional activities are among the most significant aspects in ensuring continual visits and engagements from visitors to heritage sites and institutions, including museums. An ineffective marketing technique will make it challenging to attract visitors and communities. This leads to the decrease number of visitors, undermining the fundamental mission of museums as an informal educational establishment for the public. However, few studies have been done on a promotional strategy for museum management in Malaysia. This paper seeks to bridge the gap by exploring the current museum's marketing technique, using the Kelantan State Museum as a case study. It aims to look further into the museum's promotional strategy, the involvement of responsible bodies, and the challenges in promoting the museum, specifically during the covid-19 pandemic. The research employed a qualitative design with purposeful approaches and snowballing techniques by interviewing the personnel at the Kelantan State Museum. The collected data were then analysed by applying Braun and Clarke's six-step thematic analysis methodology. The results identified three main themes: marketing strategies and activities, collaboration between stakeholders and challenges going forward. The overarching findings highlighted major stakeholders and their degree of participation in museum promotion. This paper also discussed the challenges posed by the museum management in promoting their establishment to the public. This include issues such as visitor expectations, funding cuts and digital adaptation; and the cessation of many museum hubs for physical visitations due to the Covid-19, leading to new rules being presented to adapt to the recent changes in ensuring visitors' safety. It is believed that the new norm has impacted the museum management's efforts to promote their institution, necessitating the development of new strategies to increase public participation. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2021 or COVID-19 has affected almost all individuals around the globe. Consequently, Malaysia is one of the nations that has been facing tremendous changes in various sectors due to COVID-19. As the number of positive cases is on the rise, the Malaysian government has executed its National COVID-19 Immunization Program to reduce the spread of COVID-19 and the severity of disease in case a vaccinated person is infected. However, there are also individuals who have contributed to vaccine refusal due to many factors including misinformation about vaccines, religious beliefs, lack of knowledge, and awareness. Therefore, this paper presents a combination of instructional design and cognitive load theory named CoLoMo model, to increase the awareness of COVID-19 among parents. The CoLoMo model is a theory for mobile application development involving three elements in mobile instruction design which include platform, design, accessibility, and design page. These elements have been chosen prior to the target users which are parents or adults. The three cognitive load theory types in this model are intrinsic, extraneous, and germane cognitive load. The combination of the mobile interaction design and cognitive load theory types will affect the user's cognitive performance which are concentration, learning capabilities and attributes. This paper also discusses the previous research on the implementation of cognitive load theory through mobile applications. Several strategies that emphasize different relevant cognitive processes which are useful to consider when developing mobile applications are also discussed. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has forced many higher education institutions (HEIs) to implement online learning. Various courses including entrepreneurship were conducted by using online methods, such as synchronous and asynchronous. However, the achievement of course outcomes through these two methods has yet to be examined. As such, this paper presented the level of entrepreneurial intention exhibited by university students after they have completed an entrepreneurship course through online learning method. It further compared the entrepreneurial intention level between students who attended the course through synchronous and asynchronous online learning modes. The data were collected through questionnaire survey method, in which only quantitative data pertaining to students' background and entrepreneurial intention were gathered. A total of 315 students were randomly selected from a population of full-time students who have completed an entrepreneurship course in a local university. They were required to respond to an online self-administered questionnaire. Informed consent was obtained prior to the process of data collection and responses were treated anonymously. As for data analysis, descriptive and inferential statistical analyses were performed. Specifically, mean and standard deviation were used to determine the level of entrepreneurial intention. Internal consistency was used to confirm the reliability of data. While independent sample t-test was carried out to compare the entrepreneurial intention level between students from synchronous and asynchronous learning modes. The data demonstrated that differences were found in entrepreneurial intention between the two groups of students. Therefore, it could be concluded that synchronous and asynchronous modes yielded different level of entrepreneurial intention among students. This paper provided new insight on online learning for entrepreneurship course, especially in the COVID-19 pandemic period in which most courses were conducted online. It was also useful for HEIs to assess the effectiveness of online learning in delivering entrepreneurship course. [ABSTRACT FROM AUTHOR]

Since the Covid-19 pandemic, videotelephony has become a popular communication method. Some communication, like business meetings, school classroom activities, market transactions, etc, should be replaced with online ways because of the social distancing policy. But not all people can easily use the online meeting platform. Some still struggle with bandwidth consumption of online meeting (video conference) activities. They need more low bandwidth consumption in doing video conferences because high bandwidth consumption means high costs. This paper discusses lowering video conferences based on turning on or off cameras. Because of this case, some platforms create their video conference applications. One of the popular video conference applications is Zoom Meeting. The data used in this paper are collected by using 30 computers in a laboratory. Firstly, the total time every user turns on his camera and his bandwidth consumption is investigated, every computer is set to turn on its camera for 1, 2, 3..., 30 minutes. The result shows there is no relation between them. Secondly, the number of people who turn on their cameras and the bandwidth consumption of every user is collected. All computer cameras are turned on in the first observation, and then a computer turns off its camera every three minutes. The result shows a relation with decreasing trend between both variables, but there is heteroscedasticity between them. The data is reduced until only fifteen computers turn on its camera until one computer. The result is a strong connection between both variables. It is caused by the gallery view method is using in the observation. Lastly, we recommended only speaker view in doing Zoom Meetings. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak impacted drastically to education and most of educational institutions started preferring online education for students. However, after the settlement of the pandemic there is uncertainty among people about whether they should prefer online education for furthermore or start in offline mode to make it more interactive, so this paper is about an analysis of people's sentiments and emotions through Tweets about COVID-19 Education. This paper aims to study the reaction of people around the world toward online education during COVID-19. This study is conducted on the basis of the responses of students, teachers, parents, college professors, etc. We started with labeling the data into three sentiments namely positive, neutral, and negative and for validation then we used Machine learning (ML) classifiers namely, Logistic regression, Decision tree, Random Forest, Multilayer Perceptron (MLP), Naïve Bayes, Support vector machine (SVM), K-nearest neighbors (KNN), and XG-Boost. Then we performed emotion detection by considering 5 emotions namely happy, surprise, sad, fear, and angry and for validation we used ML classifiers. After applying all these ML approaches, the XG Boost ML classifier achieved the highest accuracy of 94% in classifying the tweets as positive, neutral, or negative, and 96% accuracy in classifying the tweets as happy, surprised, sad, fearful, or angry. [ABSTRACT FROM AUTHOR]

COVID 19 disease has spread worldwide, disrupting the economy, society, education, and health. It became crucial to understand the transmission curve and identify the best action in combating this highly transmissible epidemic. Epidemiological parameters of the deterministic Susceptible-Infected-Removed (SIR) model are widely used in explaining the characteristics and behavior of the disease spreading. Disease like COVID-19 is highly influenced by the uncontrolled factors of randomness, hence in this paper, the deterministic susceptible-infected-recovered-death (SIRD) model is extended to the stochastic SIRD (SSIRD) model. SSIRD model takes into consideration the noisy behavior of the process which explains the uncontrolled effects of the COVID-19 outbreak. The epidemiological parameter of the model changes throughout the epidemic due to external factors such as enforcement and public obedience to the control measures as well as the changes in healthcare facilities. These parameters need to be estimated. This paper estimates the epidemiological parameters of the SSIRD model using the Markov Chain Monte Carlo (MCMC) method of the Metropolis Hasting algorithm. The COVID-19 data from Malaysia and Indonesia are used and the dynamical behavior of the COVID-19 outbreak in both countries is simulated. The results show the parameter changing due to the uncontrolled factors influencing the trend of the pandemic curve. [ABSTRACT FROM AUTHOR]

The implementation of Community Activities Restrictions Enforcement (PPKM) during the Covid-19 pandemic reduced activities in the transportation sector. This paper presents the measurement of Carbon Monoxide (CO) concentrations during the PPKM in Makassar City, Indonesia. The samples were collected weekly from August to September 2021 from two traffic-heavy roads using Tedlar bags and a vacuum pump and then analyzed using the Non-Dispersive Infrared method (NDIR). Results showed that the average concentrations of CO on the first street in the morning, midday, and afternoon were 826.63±83.34 µg/m3, 685.65±57.43 µg/m3, 861.6±59.79 µg/m3, respectively; and on the second street were 875.46±77.80 µg/m3, 741.80±62.95 µg/m3, 833.04±44.80 µg/m3, respectively. These CO concentrations measured during the PPKM are lower than those measured before the PPKM on the same sites, reported in another paper. The concentrations are also much lower than those of the Air Quality Standard in Makassar, 30,000 µg/m3. This finding implies that similar policies to reduce traffic and pollution, such as car-free-day, should be enacted to improve air quality. [ABSTRACT FROM AUTHOR]

Today, the world is exposed to many widespread health crises. One of these crises is the emergence and spread of the covid-19 virus, where any person becomes infected with this disease through the rapid transmission of infection between people, either by palpation or by inhaling droplets of carriers of this virus. Hence, there is a need to build a tracking system to respond quickly to problems. This paper proposes using one of the unsupervised machine learning algorithms, the K-Means Clustering Data, to determine the areas with the most significant percentage of infections by dividing them into infected and uninfected human groups. Where the infected persons are divided into three high groups (C1), medium (C2), and low (C3), and follow the path of the infected persons using Google Maps. The contribution to this paper is to support appropriate decision-making by public health authorities by predicting endemic areas and how to address problems that occur as they can use this system to reduce other infectious diseases. [ABSTRACT FROM AUTHOR]

In this proposed system we have achieved the benefit of online voting as we all know that internet and gadgets are very good. In this pandemic situation we can prefer Online Voting System instead of offline voting system. By using the Online Voting System, we can avoid the crowd, gathering and to overcome the Covid cases. For Example, nowadays people are not maintaining social distance that can causes more Covid cases. In order to save the time and life's of the citizens of nation we can prefer Online Voting System project. This paper presents an effort to leverage benefits to achieve an effective scheme for online voting. The election can be conducted in two ways: By Paper Polling form and Mechanized Voting Form. Web-based voting refers to the decisions made by robotized polling forms. The internet casting a ballot framework is profoundly evolved and the web-based surveying framework can be supplanted by precisely and legitimately casting a ballot on the web and prompt outcomes to provide the security implementation. User-based voting will benefit from this system. Both the implementation and its implementation are made up of two parts: There are two sections: one for voters and one for administrators. In these protocols, the voter segment can be found at home or work, or through a device that allows the voter to access the information and grant data authentication. It is up to the administrator section to perform or allow the functions of a voter based on validation of voter ID, candidate registration, verification and the database result. A One Time Password module is the mainly used for the security implementation. In this research, each time a user logs in to the system, a unique password is generated. Every time a user logs on to complete an operation, an OTP is sent to their registered mobile number. This OTP is made up of a series of random digital numbers, and it changes over time. [ABSTRACT FROM AUTHOR]

The paper describes the methods and tools for realizing the electronic information and educational environment of an educational institution. The paper describes the requirements for systems for monitoring and supporting the educational process. The indicators requiring attention during the functioning of the electronic learning environment are considered. The paper presented aspects of the increased system load because of covid-19 pandemic [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze students' chemical literacy through implementing an Ethical Dilemma-STEAM teaching model in chemistry acid and base lessons. The model is designed to engage students in values-based learning through dilemma stories that pose environmental problems to be solved through the development of an interdisciplinary project. The study involved 40 grade 11 students from a high school in Jakarta, Indonesia, during the 2021/2022 academic year. A qualitative research method was employed to investigate students' learning experiences through classroom observations, semi-structured interviews, reflective journals, and a chemical literacy test. The model engaged students through five steps of learning: value reflection, problem-solving and decision-making, content integration, STEAM integration, and transformation. In this study students were challenged to develop a jet-powered boat as a solution to an inter-island mobility dilemma. The study found that the Ethical Dilemma-STEAM teaching model supported students' chemical literacy development. The study demonstrated that students were encouraged to think critically by applying their conceptual understanding to practice. They were motivated to look closely at chemistry issues in everyday life, an indication that this model could be used as an alternative way to engage students to see the relevance of chemistry concepts and their application to the local environment. The paper also addresses the difficulties researchers faced in implementing an innovative approach to chemistry education during multiple COVID-19 outbreaks. [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]

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]

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]

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]

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 paper examines the dynamics of the spread of the BA4 and BA5 variants of the COVID-19 virus in DKI Jakarta Province using the SIR Model. The parameters contained in the model are assumed to change over time according to the daily case empirical data. Based on the available data, the value of these parameters is estimated using FIR filtering and viewed as an optimization problem solved by the ridge regression algorithm. The model formed is used to predict the number of cases of the spread of COVID-19 for the next few months. The results obtained indicate that the model can produce stable output and it is predicted that COVID-19 for BA4 and BA5 variants will subside for the next few months. [ABSTRACT FROM AUTHOR]

The extraordinary event of COVID-19 has resulted in economic shocks that have an economic impact on Indonesia. This has occurred in a variety of industries, including household consumption, investment, and financial institutions. There was a threat of loss of community income in the household sector because people were unable to work to meet their daily needs, particularly in poor and vulnerable households and the informal sector. Gardening, particularly hydroponic gardening, which has promising business potential, can help urban households overcome the economic problems caused by the COVID-19 pandemic. In recent years, one of the most popular forms of solar energy application in Indonesian urban areas has been the use of solar photovoltaic (PV) technology for water pump systems. This paper deals with the application and testing of the Photovoltaic Water Pumping System for Hydroponic Plants to Support Small businesses in the urban areas of South Jakarta. The system consists of two (2) PV modules Sun Asia Model SP 100 – 18M are wired in parallel, the electronic components and cables, battery bank, the submersible motor-pump set, and the hydroponic plant and its accessories. From the testing, it was found that the average capacity, head, and hydraulic power of the pump are 14.82 LPM, at 11.35 meters, and 27.337 Watt respectively. The overall pump efficiency is 31.19 %. Based on the investment criteria, it is possible to conclude that the application of the Photovoltaic water pumping system for hydroponic plants is feasible because the NPV is positive, and the Benefit-Cost Ratio is greater than one. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to prepare the most commonly used cluster analysis; hierarchical and non-hierarchical cluster analysis algorithms which are the K-means, the Partition Around Medoids (PAM) and the agglomerative hierarchical, to group 37 African countries on the basis of measures of COVID-19 cases, economic development and general health resources. We found that the optimum number of clusters is four and countries like Morocco, Algeria, Libya, Gabon, Botswana, Tunisia, Mauritius, and Seychelles are grouped together into one cluster, and how Egypt and South Africa formed another cluster. A Hierarchical clustering was found to be more precise compared to the other two algorithms. [ABSTRACT FROM AUTHOR]

COVID-19 disease is caused by a contagious family of corona virus. The dynamics of infectious novel virus SARS-Cov-2 is studied in this paper. We have studied a 7 class Susceptible-Exposed-Vaccinated-Asymptomatic Infected-Symptomatic Infected-Hospitalized-Recovered (SEVI1I2HR) model. Local stability for the equilibrium pointsis established with the help of Routh Hurwitz criterion. Proof of Global stability of the endemic equilibrium is done with Dulac's function. Numerical simulation carried out for the model suggests that minimizing the contact rate, hospitalization of the infected and vaccinations for all are the only ways to control the pandemic COVID-19. Sensitivity analysis of the considered parameters in the Basic Reproduction Number (R0) was performed to understand the most affected and sensitive parameters of the model. It was observed that R0 is directly proportional to the contact rate while inversely proportional to vaccination rate. [ABSTRACT FROM AUTHOR]

In this paper a mathematical model is developed to identify the meantime to respiratory failure in Covid-19. According to this model the respiratory failure occurs whenever the total number of damaged cells in lowers respiratory and air sacs in lungs of the infected exceeds their corresponding thresholds. Due to uncertainty, these parameters are considered as random variables. The performance measures of respiratory failure are derived by assuming suitable distributions for the random variables. Finally, the performance predictions are numerically illustrated. This study will help to predict the number of affected who needs ICU and also it creates awareness to peoples, which would helps to reduce the spread of Covid-19. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) outbreak from Wuhan, China has spread very quickly in the world and caused many deaths. In Indonesia, the first case of COVID-19 was reported by the government in March 2020 then it became a pandemic disease. Estimating case increase rate (CIR) and case fatality rates (CFR) are important parameters for studying the basics of pandemic disease. In this paper, we analyse the case increase and case fatality rates of COVID-19 in Indonesia based on longitudinal data and average temperature by using biresponse local linear estimator. The characteristics of case increase and case fatality rates of COVID-19 in each province are different, so locally modeling is more appropriate. The result shows, on average, the highest rate of case increase was in July 2020 and the highest rate of case fatality in August 2020. This happened because of government policies that loosen social distancing programs and increased human mobility due to the holiday in the previous month. Based on average temperature, in November 2020, there were the lowest decreassing CIR and the highest increassing CFR because in November, it entered the rainy season which makes the average temperature lower. It means that the number of COVID-19 cases will be higher if the average temperature is lower. [ABSTRACT FROM AUTHOR]

The study in this paper analyzes the model of the spread of COVID-19 in Papua Province. The population is divided into five subpopulations, namely Suspected (S), Infected (I), Independent Isolation (Q1), Isolation provided by the Regional Government of Papua Province (Q2), and Recovered (R). Parameter values were obtained from COVID-19 data for June-August 2021 in Papua Province. The method for estimating the parameters in the model study uses the least square fitting technique and some of the parameters are taken from other journals, with data sources in Indonesia. Model analysis determines non-endemic stability points, and endemic models determine reproduction numbers. The model analyzed local and global asymptotic stability. The model solution is solved by using the fourth-order Runge-Kutta method. [ABSTRACT FROM AUTHOR]

Hand Gesture is a form of nonverbal interaction communication and can be used for various applications, communication between deaf-mute people, human-computer interface (HCI), robot control. The COVID-19 pandemic has made it extremely difficult to instruct kids online while keeping the class engaging. Children needed a classroom that was free of dust as a result. This research paper shows a special sketch application that recognizes hand motions and keeps track of hand joints. This programme employs hand gestures to provide users with a natural way to interact with computers (HCI). Because the drawing is done in the air, the paint application becomes virtual. The UI is used to create the virtual paint screen. The webcam is utilized to extract the hand gestures and achieve fast and stable gesture recognition in real time. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has prompted an urgent need for reliable and efficient diagnostic tools to combat its spread. Since its origin in 2019, researchers have been trying to find out effective methods for identifying and classifying COVID-19 from other similar disease like pneumonia. This review paper gives a comparable overview of various diagnostic techniques employed by various experts. Artificial Intelligence (AI) based methods, like Machine Learning (ML) and Deep learning (DL) have widely been used for predicting COVID-19. These models usually generate good accuracy rates but still there is a scope of improvement. Hence, attention was shifted towards hybrid approaches which show better detection accuracy results then individual AI models. However, both AI and hybrid models overlook human social connections and migration patterns, which are diverse and not well-mixed in populations. COVID-19 modeling should consider the heterogeneity of individuals, especially as it disproportionately affects the elderly and those with underlying medical conditions like cancer, heart disease, diabetes, and hypertension. Furthermore, people's mobility patterns and behaviors significantly influence virus spread dynamics. Therefore, role of multi-agent systems (MAS) comes into play, wherein each agent represents different data or information. However, not much work has been done in this filed and hence it needs to be explored more in future studies. Furthermore, it was noted that a significant proportion of researchers favored the utilization of CNN and its variants and SVM classifiers, while a minority opted for RF and regression models for the purpose of classification. Overall, this review provides insights into the strengths and limitations of each approach, emphasizing the need for a comprehensive strategy that harnesses multi-agent systems for COVID-19 detection. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT)-based health monitoring devices may be very helpful for COVID-19 pandemic patients. The main goal of patient monitoring in post-covid life is to have a quantitative assessment of the vital physiological markers of patients. An IoT-based health monitoring and surveillance system is presented in this paper after the COVID pandemic. This device monitors a patient's oxygen saturation level, heart rate, temperature, pulse rate, and systolic and diastolic blood pressure. New evidence suggests that ML and AI approaches could considerably mitigate the viral attack. In this article, we establish a collaboration between an IoT system and a machine learning prediction model to keep tabs on people's health in the post-COVID age. The algorithm's severity forecasts for patients were very accurate, taking into account a number of criteria including laboratory data and vital signs. The data was analysed using two classification techniques: random forest (RF) and support vector machine (SVM). Multiple techniques were used to pre-process the data. Outperforming the SVM, RF achieved a score of 0.956. [ABSTRACT FROM AUTHOR]

On data that are not normally distributed, classical linear regression is developed into the Generalized Linear Model (GLM). One of them is logistic regression which is used for binary discrete data. A different strategy is to consider all variables (response and predictors) to be random observations from the joint probability distribution. A model with dependencies should be used because some factors are dependent. The copula model, one of which is the Gaussian copula, is a popular technique for creating multivariate models with dependencies. The Gaussian copula regression model (GCMR) is a general structure that can be used to model any form of dependent response. The Gaussian copula blends the ease of interpretation of marginal modeling with the flexibility of the dependency structure specification. In this case, the estimated parameter is the regression coefficient and the error is expressed in the dependency structure. The model estimation uses the maximum likelihood method. This paper aims to apply the GCMR model to time series data where the dependent variable is discrete with a binomial distribution. A case study was conducted to see the effect of weather factors on Covid cases in DKI Jakarta. The regression model used is binomial data logistic regression with the dependency structure expressed in the correlation matrix with the assumption that the error is obtained from the ARMA(p,q) process. The dependent variable is the number of Covid-19 cases and the independent variable is the maximum temperature, average temperature and humidity. The data are a daily time series with a range of March 1, 2020 to April 30, 2022. Based on the GCMR model, Maximum temperature, average temperature and Humidity have a significant influence on the number of Covid-19 cases in Jakarta. For this case study, the results show that the GCMR model is better than logistic regression analysis. [ABSTRACT FROM AUTHOR]

Covid-19 is a severe pandemic with a high mortality rate caused by the infectious respiratory virus SARS-CoV-2. Viruses associated with respiratory tract infections will use epithelial cells and airway mucosa as initial targets and cause respiratory tract infections or organ damage. This paper develops a model for the spread of Covid-19 with the effect of vaccination and quarantine. This model has seven variables, namely Susceptible, Vaccinated, Exposed, Symptomatic, Asymptomatic, Quarantined, and Recovered. From this model, two equilibrium points are obtained, non-endemic and endemic equilibrium points. Further, we analyze the global stability using the Lyapunov method. If basic reproduction number (ℛ0) less than one, then the non-endemic equilibrium point is globally asymptotically stable, while if basic reproduction number more than one, then the endemic equilibrium point is globally asymptotically stable. Numerical simulations are given to describe the behavior of the spread of Covid-19 in Banten Province on February 1, 2022 until May 1, 2022 with the result that increasing vaccination rates can reduce susceptible subpopulations. From the simulation results, it is obtained with a value of ℛ0 = 0.0000103<1, meaning that the Covid-19 spread model is asymptotically stable at a non-endemic equilibrium point. This indicates that the spread Covid-19 will decrease over time. [ABSTRACT FROM AUTHOR]

We describe an existing co-dynamics model of the spread of malaria and COVID-19. Mathematical model can be used to find strategies to control the spread of malaria and COVID-19, so that their spread can be minimised in a population. The mathematical model we use is of the type of the SEI (Susceptible-Exposed-Infected) model for malaria and COVID-19 co-dynamics. For this model, we have three compartments of the human population and three compartments of the vector population. The compartments are based on S (Susceptible subpopulation), E (Exposed subpopulation), and I (Infected subpopulation). Solutions to this mathematical model can be obtained using numerical methods. We use the third-order and the fourth-order Runge-Kutta methods to solve the co-dynamics model. From our simulation results, both methods perform quite well. The fourth-order Runge-Kutta method theoretically has a higher accuracy than the third-order one. Our simulations in this paper confirm that, when solving the SEI model of the spread of malaria and COVID-19, the fourth-order Runge-Kutta method performs better than the third-order Runge-Kutta method. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic problem has had a negative impact on many individuals, and as a result, there have been fatalities since there are no artificial ventilation systems. In this regard, this paper offers a suggestion for the strong electromechanical ventilator design and operation of a non-invasive, inexpensive ventilator, In this work, a strong mechanical motion control system is proposed, ensuring control of the tracking of the corresponding path of Patients' necessary breathing patterns. Results from experiments and simulations show the efficiency of the prototype's suggested design using a program ANSYS, however, the prototype is awaiting testing and approval for use in health assistance. [ABSTRACT FROM AUTHOR]

In this paper, the population was divided into seven subpopulations, namely susceptible (S), vaccination (V), exposed (L), infected not reported (I1), infected reported (I2), quarantine (Q) and recovered (R) subpopulations. Analytical study on the COVID-19 model, to determine the non-endemic equilibrium point, reproduction number, and system stability. The model solution was determined by numerical analysis, and model sensitivity analysis by changing the values of the vaccination rate and treatment rate parameters. Based on numerical simulation results, if the value of the vaccination parameter or the value of the treatment parameter increases, the number of individuals in the subpopulation infected with COVID-19 decreases, and the number of individuals recovered from the subpopulation increases. [ABSTRACT FROM AUTHOR]

The outbreak of the novel Coronavirus has taken the lives of many and has increased the demand for new and innovative medical and testing equipment. In addition to that, the longing to retain normalcy, during these difficult times, is also required. Industry 4.0 is the contemporary phase of the Industrial revolution whose backbone is 'cyber-physical' systems. It is automation of the conventional industrial and manufacturing processes using the latest technology. This paper aims to show an in-depth evaluation done on the technologies of industry 4.0 and their implementation during the Covid-19 pandemic. It also gives an overview of the major technologies used and their range of operation, towards making societies better and saving lives. [ABSTRACT FROM AUTHOR]

The present study is about the detailed analysis of the pandemic Corona Virus 2019 which has rocked the entire world with a maximum impact with its structure, its appearance and nomenclature, Clinical presentation and transmission, diagnostic technique. It's a respiratory illness caused by the virus SARS-CoV2 (Severe Acute Respiratory Syndrome). It's a syndrome is different from other virus syndromes as this might act as Symptomatic also as Asymptomatic. The common symptoms would be cold, fever, cough, sneezing, running nose, breathing issues, Fatigue, etc. The paper may be a vivid picture on the COVID 19 cases in Tamilnadu which is within the Southern part of India and therefore the treatments like Ventilator, Plasma, etc and therefore the remedy offered to the patients like Naturopathy, Ayurvedic, Siddha, Unani, Homeopathy, etc,.for better recovery and immunity to fight against the virus. It analyses the detailed reports and statistics during a regression form with reference to daily new death rate and total death rate with the assistance of statistical tools of the general rectilinear regression equation. the entire confirmed cases and daily new confirmed cases are plotted using Normal P-P plot of regression Standardized Residual. The Pearson correlation value is 0.837 which features a strong direct correlation between active cases and total recoveries. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study of the trends in banking services. The consequences of the severe post-Covid-19 crisis and the isolation have had a strong impact on all areas of business. This has led to a rapid digitization and implementation of smart bank branch technology, aiming at saving financial resources. Transactional models, representing the participants in a mobile payment transaction, as well as the connections, by means of which the communication takes place, are considered. The application of artificial intelligence in the bank activities and in the activities of the new bank branches is analyzed. The trends for future development of both the bank branches and the banking operations are outlined. [ABSTRACT FROM AUTHOR]

Financial markets were the first to react on COVID-19 pandemic and were also very sensitive on following lock-outs, support policies and restrictions. Though equally exposed to the threat and lack of information, different countries reacted to the disease in a different way. In this paper we focus on European financial markets and respective representative indices to analyze their characteristics and study their response to the economic changes that followed the outbreak of the pandemic. We use six European stock market indices (FTSE 100, CAC 40, DAX, IBEX 35, FTSE MIB and STOXX Europe 600) to compare their performance before and after 2020, assess their reaction on COVID-19 and discuss their recovery. Using MLE estimation and BFGS optimization we analyze return distribution and use them as proxy for pandemic impact. [ABSTRACT FROM AUTHOR]

The goal of this study is to outline the outcomes of analysis on the creation of useful math learning resources during the COVID-19 pandemic. The issue is that goods from the creation of math learning resources are required to counteract an acceleration in learning following the COVID-19 epidemic. Many of the results of development research, however, are only kept as study materials and are only preserved in Study Program documents or on Google Drive. The study was conducted utilizing the survey methodology, questionnaire data collection strategies, and development research outcomes papers completed by students of the Mathematics Education Study Program FKIP UPGRI Palembang during the COVID-19 epidemic. strategies for analyzing quantitatively described data. The outcomes of the development research take the form of products for math learning devices, with PBL/PBM, RME, CTL, and mathematics software being the most widely utilized learning models and methods. E-modules, LKPD/LKS, learning media in the form of video, and PPT are the most common product kinds. Algebra, Geometry, Calculus, trigonometry, statistics, and Arithmetic are among the mathematics topics covered throughout the development. The development's validity yields a product quality of 87.19%, while its practicality comes in at 85.48% and its potential impact is at 83.48%. According to the development research's findings, it should be given some thought if mathematics instruction is to be changed following the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Mobile payments (M-payments) refer to the deployment of mobile technologies to perform transactions. This paper develops a conceptual model for shoppers' M-payment technology innovation readiness and adoption during the Covid-19 pandemic. The model incorporates the Technology Readiness Index (TRI) as a determinant of the Technology Acceptance Model (TAM) to create a framework that contains readiness characteristics (contributors and inhibitors) affecting users' adoption and acceptance of M-payment technologies. This unified model presents mobile payment adoption as a process progressing from the antecedents of the TAM to the adoption decision. [ABSTRACT FROM AUTHOR]

The devastating effects of the COVID-19 global pandemic has forced most business transactions to shift from the conventional approach to the online medium to ensure their sustainability during this critical period. Artists are also transforming their approach from physical exhibitions to virtual exhibitions to ensure their business sustainability. Conventional or physical exhibitions draw large audiences; however, due to the COVID-19 global pandemic, such gatherings are strictly prohibited. Thus, virtual museum exhibitions will continue to be organised in the future, therefore, knowledge about factors that affect virtual exhibitions will be in demand. This review paper intended to examine the predictors that influence viewers' satisfaction in Virtual Art Exhibition. A comprehensive literature survey was carried out from March to May 2021 and the reviews reveal that there are three factors that possibly influence viewers' satisfaction, which are the technology, aesthetic value, and individual factors. This review study has outlined the fundamental aspects that will serve as a guideline for artists by considering the technology, aesthetic value and individual factors in preparing for future virtual exhibitions as well as in improving viewers' satisfaction. [ABSTRACT FROM AUTHOR]

In the last month of 2019, a new coronavirus has been discovered. The coronavirus (COVID-19) pandemic already has caused major human suffering as well as significant economic loss. The rapid spread of this disease all around the world has made every country to implement lockdown in order to break the chain of Covid-19. The imposed of lockdown in every country all around the world have given a major impact towards political, social, human suffering as well as significant economic disruption. The COVID-19 pandemic has flipped the world of work all over the sides. It having a significant impact on workers' and their families' jobs, lives, and well-being, as well as on businesses around the world, particularly small and medium-sized businesses. This paper aims in exposing the effect of COVID-19 on the economic as well as in the employment globally. As a result, there are a lot of effect from the movement restriction order that have been imposed by the government in each nation. The imposed on movement control order with the implementation of stay at home policy and social distancing have impacted all sectors of economic which has led impact the employment. [ABSTRACT FROM AUTHOR]

The Indonesian government has taken several policies to break the chain of transmission of the COVID-19 virus infection since the spread of this virus variant was first discovered in March 2020 in Indonesia. One of them is to require everyone to get vaccinated. This national vaccination program has been started since early January 2021 until now and expected to be one of the solutions to control the spread of coronavirus in Indonesia. This paper presents robust k-means to show the cluster of the spread of COVID-19 in Indonesia after the implementation of the vaccine policy for Indonesian citizens. The k-means algorithm is an unsupervised machine learning method. This method is well known in clustering. This is a partition clustering algorithm which is widely used in practice but in general, this method is sensitive to the presence of outliers. The variables considered in this study are the number of deaths, the number of recovered patients and the number of patients. Experimental comparisons are made with the basic k-means and robust k-means algorithm. It seems that for data on May, 2021, the cluster with k=3 in the robust case will provide closer risk levels of the provinces in Indonesia with their risk in reality, namely provinces with high, mid and low-level risk. [ABSTRACT FROM AUTHOR]

Coronavirus Disease (COVID-19) pandemic has emerged as one of the biggest challenge faced by researchers, especially in public health system. Since the virus spread and mutates quickly, strategies are needed so that the public health system doesn't collapse due to overcapacity. Modeling and forecasting accurately the COVID-19 daily new cases is very important to understand and help carry out risk management for the outbreak control. To obtain the estimation of the Indonesian daily cases of COVID-19 based on daily confirmed cases, we present a comparative study between three deep learning methods in this paper: Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Convolutional Long Short-Term Memory (Conv-LSTM). The data used is daily confirmed cases from September 1st to September 7th, 2021. The result is Conv-LSTM model produces better performance than other methods. Here we also provide 7 day out-of-sample forecast for daily cases from September 1st to September 7th, 2021 using each model. [ABSTRACT FROM AUTHOR]

The global crisis brought on by COVID-19 is unparalleled. Tourism is one of the many industries that have been made public by the recent COVID-19 epidemic. Indonesia itself was affected by the impact that caused a decrease in both foreign and domestic tourists. Smart tourism through the metaverse concept is one of the proposed solutions to deal with this problem, considering that metaverse has been booming lately, so it can attract the attention of tourists who cannot come directly to the tourist attractions. This paper aims to provide new insights regarding how to improve the Indonesian economy through tourism, so people realize the importance of the metaverse in the future. Moreover, we believe that the future of this metaverse will be very bright because the advantages of technology used in the metaverse are very beneficial for users (Blockchain, Crypto, Non-Fungible Token). [ABSTRACT FROM AUTHOR]

The global Covid-19 pandemic has significantly impacted various sectors in Indonesia. One sector that has a significant impact is the tourism industry, especially amusement parks and theme parks. Not much can be expected to attract visitors during a pandemic with just a regular touring video, even though the amusement park maintenance must still exist. This paper aims to develop an Augmented Reality (AR)-based Dino Park application with Unity and the SCRUM development method. This AR application was created aiming to increase user interest and experience to come to this place, such as virtual touring with AR features, providing a tourist sensation with 3D visuals because it can be moved according to the user's wishes and it is as if they have a virtual guide with information in the form of audio contained in each dinosaur fossil. The results of this study are Based on the results of the user acceptance test, an average of 83% user satisfaction levels with details (85% stated that the application is interactive to use, 83% stated the display is very attractive, 81% of the Dino Park application is very useful for people in in the field of theme park tourism, and 84% state they were satisfied with this application compared to similar applications in terms of features and appearance). [ABSTRACT FROM AUTHOR]