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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]

In this paper, the spread of the Covid-19 in.Indonesia is described by the SIRD epidemiological mathematical model. The mathematical model used in this paper is Susceptible, Infected, Recovered, Death (SIRD). The modified extended Kalman filter algorithm is applied to predict the spread of Covid-19 in.the future. We modified the algorithm by generating real data based on the previous estimation results. The real data generated from the generation is used at the correction stage to obtain prediction results in a fairly long period. Simulations were carried out with three types of mobility restrictions, namely mobility 100%, mobility 75%, and mobility 50%. Based on the simulation results, it can be concluded that mobility restrictions in Indonesia, which starts on September 4, 2020, can reduce the number of infected and death individuals and can increase the number of individuals who recover from Covid-19. [ABSTRACT FROM AUTHOR]

Investing in the stock market involves inevitable risk, especially due to the Coronavirus disease (Covid 19) and regional quarantine (lockdown) policies. Experiencing pandemic conditions, some investors might be worried and sold their stocks. Any action would make some loss or miss potential significant gain. Even though time the market is considered a hard and complicated process, understanding the risk can be one way to quantitatively measure the risk. In this paper, the risk is quantified using Monte Carlo simulation by considering Covid 19 outbreak where the expected returns and the highest values were observed. Furthermore, Analyzing Process use data from three different coal mining companies in Indonesia stock exchange. As a result, the three stocks presented which stock was the most, moderate, and least risky. [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]

This article examines online test monitoring technology, which has been under public attention due to school lockdowns during the COVID-19 pandemic, which has increased the demand for online courses. Cheating on educational assessments is a worldwide issue; it happens in online and face-to-face courses, and it is prevalent among students taking unsupervised online examinations. Several online proctoring tools have emerged in the market, providing solutions to some key challenges. Some of these online proctoring tools use Auto proctoring systems. With the sudden condition like Covid 19, the online proctoring tool has not been tested on a large scale for the conditions in Indonesian vocational high schools. The service fee and technical requirements are included in the trial in question. This paper describes one of the first attempts to evaluate the selection of this tool properly and makes recommendations for secondary schools in Indonesia. This investigation, carried out at the Sragi Vocational High School, was divided into several phases, beginning with a literature review and ending with a pilot test conducted by a group of experts and students. The elimination of tools in each phase is based on the "survival of the fittest" approach, with each phase building on the previous phase's achievements and results. It has been shown that Auto Proctoring on Unsupervised Exams has a favourable impact on teacher assessment. [ABSTRACT FROM AUTHOR]

Lockdown is one of the policies taken by many countries to prevent the spread of covid 19. In contrast to other countries, Indonesia does not adopt a lockdown policy but prefers Restrictions on Community Activities (PKM). Restrictions on community activities such as referring to lockdown but not in full, the existing policies include four restrictions: cessation of the implementation of activities in schools and educational institutions, restrictions on activities at work, restrictions on religious activities, and restrictions in public places. This paper tries to investigate the effect of restrictions on Community Activities on air quality, especially on the concentration of Carbon Monoxide in one city and partially based on core activity. This study measures the column concentration of total Carbon Monoxide (CO) from the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite. In this study, we analyze the average CO concentration of Semarang City before and during COVID-19 from January 1, 2019, to August 30, 2021. The results show that the policy of restrictions on Community Activities can reduce the value of CO concentration to remain stable at < 30 mol/m2 in core activities with the dominance of local internal transportation within the city (education, settlements, trading center, and industry), while activities with the dominance of transportation outside the city (transportation nodes) produce different things with an average concentration of > 32 mol/m2, but with a downward trend. [ABSTRACT FROM AUTHOR]

Tourism is one of the most important sectors in Indonesia. However, since the COVID-19 pandemic, tourism industries has declined significantly. Restrictions on mobility and activities in public places affect the tourism sector. One of them can be seen from the hotel room occupancy rate (ROR). ROR in Indonesia experienced a significant decline in mid-2020, since the spread of COVID-19 was confirmed in Indonesia. Until the end of 2020, Indonesia's ROR seems to have increased, but still cannot fully recover as before the pandemic. It's been a year since the first COVID-19 case in Indonesia. Various policies have been implemented by the central and regional governments in dealing with this pandemic. To find out how much ROR has improved in 2021, this paper discusses the analysis of national and provinces level ROR in January 2020-June 2021 from BPS survey and big data. These two data are compared to see how well the ROR generated by big data represents the official ROR from the BPS survey. The result from big data analysis show that majority of provinces have not experienced significant ROR improvements in 2021. The result is in line with ROR from the BPS survey, as well as the demand pattern shown from the google trends data. [ABSTRACT FROM AUTHOR]

Pollution and health have emerged in recent years as worldwide concerns. A great deal of information is communicated in order to raise human awareness of this issue. Public signage is one way to obtain this information. The aim of this paper is twofold. Firstly, this article outlines the use of Google Street and Google Maps to locate street signs linked to pollution and health issues. The second is to develop a conceptual approach into creative learning by employing digital technology in discovering and introducing students to information regarding pollution and health signs in the outdoor landscape using a novel technique and approach called Digital Linguistic Landscape Learning. It was revealed that the self-access center is the focal point for the development and use of digital technology, which provides students with the autonomy to investigate or discover solutions to the contestation of socio-cultural phenomena connected to the two key concerns in the public spheres. [ABSTRACT FROM AUTHOR]

The COVID-19's rapidly spread in Indonesia is a serious concern for government. Various government policies, such as large-scale social restrictions, which is called as PSBB, and the imposing restrictions on community activities, be called as PPKM, have been applied to slow the spread of COVID-19. These policies were supposed to control people activities in many areas, especially that will invite the crowd happening. In this paper, the control charts be explored to obtain the overview of the daily new COVID-19 cases number, which is considered as a production process. The proportion of positive COVID-19 cases be observed and monitored using P-control chart. The data used is from the specimen COVID-19 test in DKI Jakarta Province, since April 2020 to January 2021. It is obtained that the process of daily new COVID-19 cases number has not been statistically controlled. It is detected some mean shifts of proportion in some point of times. Several findings indicate an upward trend, suggesting that the proportion of positive cases COVID-19 is rising. The public's conduct in Jakarta has served as a model for the government in designing policies to tackle the spread of Covid-19. However, due to the high mobility of Jakarta residents and its lack of consistency in the region, the COVID-19 process still remained out of control. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 has struck multi-sectoral such as health, education, hospitality industry, transportation, and businesses including Small and Medium Enterprises (SMEs) all around the world. Especially when the lock-down policy was administered to anticipate the increasing number of Covid-19 victims. The mobility regulation applied have turned all people and all sectors into online and social media instead of direct interaction. This paper is intended to describe the role of social media for SMEs in Indonesia during Covid-19. The qualitative research method was conducted by providing questionnaire and interviewing SMEs from three different cities in Indonesia. The data has shown that social media has played important roles for SMEs in maintaining their business during Covid-19. This research presents insightful findings which can be will be helpful for SMEs in maintaining their business during Covid-19. [ABSTRACT FROM AUTHOR]

Conserving agricultural genetic resources (AGR) is one of state commitment to support food security and sustainable agricultural system. The pandemic of COVID-19 forced Indonesia government to issued policies which resulting on significant reduction in operational costs in AGR conservation and limitation of activities. This paper describes the proactive approach taken in IAARD-ICABIOGRAD Gene Bank to maintain the sustainability of AGR conservation during the pandemic situation. Several measures were taken including laying off some contract staff, reducing working hours, delaying plantation schedule, relocation plantation site, and optimizing on seed monitoring. The delay in plantation schedule and relocation of planting site caused of less optimal of yield in soybean and mung bean regeneration and crop failure of some accessions in rice. The lack of resources caused several activities cannot be performed. Delay of seed processing increase seed damage and inadequate rogueing during seed production cause disruption of genetic integrity of rice accessions. The optimization on seed monitoring resulted in the safely regenerated of a total of 112 rice accessions and 149 soybean accessions with very low viability. Adequate support is needed for further gene bank operational to resume the incomplete activities, to set back genetic integrity, and to set better management system. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. To prevent and slow down the transmission of this disease requires a clear information about the virus itself, the disease it causes, and how it is spread. This paper presents the application of k-means and fuzzy c-means clustering analysis to show the cluster of the spread of second-wave coronavirus disease in Indonesia. The variables considered in this study are the number of confirmed COVID-19 positive, the number of patients, the number of deaths and the number of recovered patients, using data at May 31st 2021. Based on the SSE (Sum Square Error), Silhouette index and Gap Statistics, it is founded that the best clustering is using 2 clusters. [ABSTRACT FROM AUTHOR]

Corona Virus Disease 2019 (COVID-19) is a new virus that can be contagious and its worst effects can lead to death. COVID-19 first appeared in Wuhan, China until it finally spread throughout the country, one of which is Indonesia. The spread of COVID-19 cases in Indonesia itself is quite rapid until finally the World Health Organization (WHO) designates COVID-19 cases as pandemics. Based on current conditions, this paper discuss about predict positive case data of COVID-19 at five locations in East Java (Malang City, Batu City, Pasuruan Regency, Malang Regency, Pasuruan City) using a space-time model namely Generalized Space-Time Autoregressive (GSTAR). Considering that COVID-19 is very easy to spread not only depending on the time but also the proximity between locations, the GSTAR method is good enough to be used to predict the assumption of parameters between heterogeneous locations. The estimation used is OLS with the location weight of cross-correlation normalization. The results of this study obtained the GSTAR(21)-OLS model is the best model to predict the number of positive cases of COVID-19 in.five locations in East Java by weighting the normalization of cross-correlation based on the smallest RMSE value in data out sample. Forecast results for the next 10 days of positive cases of COVID-19 in.all five locations show not very significant changes. [ABSTRACT FROM AUTHOR]

The COVID-19 is an infectious disease caused by Severe Respiratory Syndrome Coronavirus-2/SARS-CoV-2. In 2020, Indonesia is the second country with the highest COVID-19 pandemic cases in Southeast Asia. Prevention of the spread of COVID-19 is carried out by quarantining infected individuals. The spread of this infectious disease can be represented in a susceptible infected quarantine recovered (SIQR) model. We formulate a SIQR model, apply the model to COVID-19 in Indonesia, determine the pattern of its transmission, and interpret the results of the application of the model. In this paper, the data used from March 2020 to January 2021 were analyzed to obtain the parameter values. Based on the application, the pattern of the spread of COVID-19 in Indonesia during 2020-2025 shows that the number of susceptible, infected, quarantine, and recovered individuals are downward trends. Furthermore, there are still infected individuals in 2025, and this amount can be reduced if the quarantine and self-isolation process is carried out optimally. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019 (COVID-19) pandemic has become one of the biggest challenge in research community, especially in public health system. One of the challenges that encountered is how to manage the public health system so that it does not collapse because of overcapacity, while maintaining the testing, tracing, and treatment to slowing down the spread of the virus and decreasing the number of deaths caused by COVID-19. Therefore, a predictive model that can estimate and forecast the new daily cases and daily deaths of COVID-19 are important to give recommendations to policy maker about how to control – and eventually – prevent the spread. In this paper, we present a comparative study between Long short-term memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Deep Bidirectional LSTM (DBi-LSTM) to forecast the number of COVID-19 daily cases and daily deaths in Indonesia, based on daily confirmed cases and daily death cases from August 26th, 2020 to August 25th, 2021. The result is DBi-LSTM performs better than LSTM and Bi-LSTM in both daily cases and daily deaths datasets, in terms of training process and lower error prediction value based on MAE and RMSE. Here we also provide 14 day out-of-sample forecast for daily cases and daily deaths from August 26th to September 8th, 2021 using each model. [ABSTRACT FROM AUTHOR]

The striking global transmission of COVID-19 has empowered numerous governments to intervene in order to keep the contamination at bay. Medical tourism could be a developing marvel with arrangement ideas for wellbeing frameworks, particularly in goal countries. Medical tourism, a rapidly growing industry, has been identified as a potential source of financial diversification by a number of countries. This study proves that government expenditure is significantly affected by CO2 emission and sectors, all in contributions to pollution. Despite the fact that Indonesia is one of the most popular destinations for therapeutic tourism, research into its competitiveness has been limited and limited in scope. This case study employs a quantitative approach to identify and analyse the variables that position Indonesia as a viable medical tourism destination. Based on an all-inclusive approach, this investigation discovered that coordinating various procedures for restorative tourism advancement with sound government arrangements and proactive administration practises has resulted in significant positive results toward shared victory of Indonesia's tourism and healthcare segments. [ABSTRACT FROM AUTHOR]

Transmission of the coronavirus continues to increase in many areas since the pandemic occurred. The increase in cases is due to the high level of transmission through droplets that can occur due to physical contact and communication made by Covid-19 sufferers. Face-to-face relationships between pharmacists and patients are vulnerable to the spread of Covid-19. Therefore, through the appeal of the Ministry of Health of the Republic of Indonesia by utilizing information technology as a medium in communicating with patients, a Communication, Information, and Education (KIE) information system was created. The purpose of this research is to produce a KIE information system as part of the duties and responsibilities of the pharmacy in terms of providing drug information. The research method with the prototype method starts from system requirements analysis and system design. The system requirements analysis interview was conducted using the PIECES method and made a system design using context diagrams and Data Flow Diagrams (DFD). The data taken is in the form of points submitted by the pharmacy in conducting KIE. This study uses data from interviews and observations of KIE points at the Pundong Clinic. The results showed that there were 8 main points conveyed by the pharmacy in conveying information on drug use to patients. The design of the KIE information system using the PIECES method resulted in a new system that can assist pharmaceuticals in conveying information on drug use to patients accurately, completely, and avoiding the transmission of Covid-19. [ABSTRACT FROM AUTHOR]

The spread of the Covid 19 virus in various countries, including Indonesia, has made face-to-face teaching difficult to implement. In a short time, schools and universities have to change their learning methods to online learning. Bina Nusantara University has prepared online learning models, such as Video Conference (VC), Video-based Learning (VBL), and discussion forum. VBL has been prepared before the lecture starts so that students can study the material first. With the VC model, Lecturers give lectures through the Zoom application. Meanwhile, the discussion forum is a means of discussion between lecturers and students through a system called Binusmaya. From these three learning models, researchers will focus on VC and VBL methods. This study aims to evaluate the two learning models regarding language proficiency skills. The research scope will be limited to the Japanese skills course at Bina Nusantara University. The data collection method in this study used a questionnaire with a 5-point Likert scale. Furthermore, the questionnaire results will be analyzed by quantitative methods using Lisrel to find the benefits of learning with these two methods. From the evaluation results, it is found that the VC and VBL methods affect Japanese Language Proficiency. [ABSTRACT FROM AUTHOR]

The crew is a profession that plays an important role in developing the national maritime industry and becomes a valuable human resources asset in operating vessels for PT. Jasindo Duta Segara company, as crew manning agency. The Covid-19 pandemic in Indonesia had a huge impact on the PT. Jasindo Duta Segara company handled the crew change process to the vessel. The Covid-19 pandemic has caused PT. Jasindo Duta Segara company faced problems in the crew change to the vessel. The research method used is qualitative. Collecting data through observation, literature study, documentation, and interviews. Validity method with triangulation technique. Data analysis methods are data reduction, data presentation, concluding. This research aims to determine the problems that occur in the crew change to the vessel and strategies taken as an effort to prevent onboard crew delays during the Covid-19 pandemic. Tthe problems faced by PT. Jasindo Duta Segara in the process of the crew change to the vessel during the Covid-19 pandemic are the crew's level of interest in working on the vessels during the Covid-19 pandemic has decreased, entry access in several countries in the world is closed (lockdown), the United States Embassy in Indonesia is closed, and the implementation of Large-Scale Social Restrictions instructions (PSBB) in Indonesia. The strategies carried out as an effort to prevent onboard crew delays are providing motivation and instruction to the crew that can return to an extension of the crew contract period on the vessel, nomination the crew on the vessels that have routes in Asia, and the implementation for the employee work shift in PT. Jasindo Duta Segara company is held on a scheduled basis. [ABSTRACT FROM AUTHOR]

COVID-19 is an infectious disease that has spread to countries in the world, including Indonesia. A stochastic SIR model was constructed to represent the spreading of COVID-19. One of the popular methods in a heuristic search and optimization algorithm, a genetic algorithm method, is implemented to estimate the parameters of the SIR stochastic model. As a result, using the parameters obtained, the stochastic SIR model can be in line with the actual data, and we get accurate predictions within four weeks later. [ABSTRACT FROM AUTHOR]

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