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.
Bogor Regency; COVID-19; Gaussian Process; Linear Regression; Random Forest; Decision trees; Gaussian distribution; Gaussian noise (electronic); Mean square error; Random forests; Gaussian Processes; High probability; Linear regression methods; Process methods; Regression forests; Root mean square errors; Time series forecasting models; Forecasting
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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