The SARS-COV-2 Novel Coronavirus, which first surfaced at the end of 2019 and caused a pandemic of a respiratory ailment known as COVID-19, was named after the SARS virus. In Indonesia, a case of COVID-19 was reported on March 2, 2020, and it was the first instance of the virus in the country. In Indonesia, the spread of COVID-19 has been very rapid due to one factor: a lack of understanding regarding COVID-19 prevention and early identification among the population. This research will address a system that will offer the most up-to-date information on the evolution of the COVID-19 case in Indonesia and will assist the community in conducting an independent detection of COVID-19 using an expert system, both of which will be discussed in this study. The information that will be presented on this application later on was gathered using web scraping methods from the official website of the task force for the acceleration of COVID-19 handling in Indonesia, which can be accessed here. An early detection function is also included in this system, which makes use of the rule basis approach expert system. In this system, the results are derived from the replies of respondents, with a percentage of 95.12 percent received from respondents who were interested in this application. Testing on the validation of the expert system's outputs yielded results that were consistent with expectations. The SARS-COV-2 Novel Coronavirus, which first surfaced at the end of 2019 and caused a pandemic of a respiratory ailment known as COVID-19, was named after the SARS virus. When this illness infects individuals, it may manifest itself in a variety of different degrees of severity. Only minor complications, such as pneumonia and a high risk of organ failure, may develop, and in severe cases, death can result.
It is impossible to isolate the rising number of verified COVID-19 cases in Indonesia from one issue, namely a lack of public knowledge of COVID-19 mitigation and early detection practises. Currently, the community is in desperate need of COVID-19 preventative and mitigation information in order to prevent the virus from spreading further. Every individual must be able to do an independent detection in order to determine how dangerous he is infected with COVID-19. This may be accomplished by early detection utilising an expert system that is implemented in a mobile application. Currently, technical advancements have given advantages for people in the form of solutions to challenges they encounter. It is one of the rare human issues that can be handled with the help of an expert system, and it is the diagnostic of COVID-19 risk. It is anticipated that the expert system in this application will assist the community in conducting early detection of COVID-19 infection risk via the use of a rule-based technique. In order for the general public to be aware of COVID-19 case creation and mitigation, web scraping methods may be used to show this information on a mobile application. This is because obtaining information through mobile is more efficient than getting information via websites.
This is a Web Scraping Services for Malaysia tourist data. Because collecting data is time-consuming and difficult, most public tourism data on the internet has been overlooked for its value. In order to gather public tourist data on the Internet, this initiative is prompted. Those who desire to construct their own web scraper may learn from this project's technique, idea, and design. On the technical side, this project uses agile System Development Life Cycle (SDLC) approach. This project focuses on gathering public tourist data from travel websites by targeting their HTML code structure. Thus, this project will show how to analyse a website's HTML code structure and identify certain elements for data extraction using HTML locator. This project will also explore the best programming language, libraries, tools, and frameworks. Because this project is in Python, you will learn how to create a basic user interface and how to store the collected data in a csv file. This project also covered data pre-processing because extracted data attributes may have too much text. The project will also investigate and execute the most suitable testing technique. Finally, a backup and recovery strategy will be outlined in case of system failure. A web scraping system particularly built for Malaysia tourism will be created to make the collection of tourist data easier and to help the tourism industry and government enhance Malaysia tourism.
W. Wiguna et al. [2] propose an expert system research using the C4.5 algorithm with the goal of obtaining a diagnosis from the surveillance category which includes Patient under Supervision (PUS), Person in Monitoring (PIM), and Person without Symptoms (PWS) according to a prevention manual and control of COVID-19 from the Ministry of Health in the Republic of Indonesia.
An expert system based on the internet was suggested by F. M. Salman and colleagues [3] to diagnose COVID-19 utilising a website-based expert system. This method shows the illness symptoms, the day on which the symptoms will be recognised, the disease's survival and spread, favourable circumstances, and a picture of the disease symptoms, among other things. In order to perform early identification of COVID-19, an expert system was developed utilising the clips and Delphi programming languages, which was then deployed in the study. The findings of an expert system that is simple to use for physicians and other individuals who are interested in coronavirus to recognise and diagnose symptoms that may be experienced or felt are presented here.
According to H. Kang et al. , an investigation on the diagnostic ability of CT scan characteristics for COVID-19 was recommended. We build a unified latent representation that can entirely encode information from distinct aspects of features while also being provided with a promising class structure for separability in order to thoroughly investigate the many features defining CT images from different perspectives. It was determined that the patient had COVID-19 and community-acquired pneumonia as a consequence of this investigation, and that the diagnosis was made (CAP).
While in this research, we propose to develop a mobile application that may assist users in diagnosing the early signs of COVID-19 risk indicator cluster by using an expert system rule-based technique to identify risk indicators. In that case, it will be easier for individuals to find out the most recent information regarding COVID-19 in Indonesia.