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Analysis of Prediction Data for the Third Wave of COVID-19 in Bogor Regency
2021 International Conference on Artificial Intelligence and Big Data Analytics, ICAIBDA 2021 ; : 66-70, 2021.
Article in English | Scopus | ID: covidwho-1774632
ABSTRACT
The COVID-19 pandemic is far from over. The government has carried out several policies to suppress the development of COVID-19 is no exception in Bogor Regency. However, the public still has to be vigilant especially now we will face a year-end holiday that can certainly be a trigger for the third wave of COVID-19. Therefore, researchers aim to make predictions of the increase in positive cases, especially in the Bogor Regency area to help the government in making policies related to COVID-19. The algorithms used are Gaussian Process, Linear Regression, and Random Forest. Each Algorithm is used to predict the total number of COVID-19 cases for the next 21 days. Researchers approached the Time Series Forecasting model using datasets taken from the COVID-19 Information Center Coordinationn Center website. The results obtained in this study, the method that has the highest probability of accurate and appropriate data contained in the Gaussian Process method. Prediction data on the Linear Regression method has accurate results with actual data that occur with Root Mean Square Error 1202.6262. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 2021 International Conference on Artificial Intelligence and Big Data Analytics, ICAIBDA 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 2021 International Conference on Artificial Intelligence and Big Data Analytics, ICAIBDA 2021 Year: 2021 Document Type: Article