Syaka, Annisa Khodista
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Journal : Applied Information System and Management

Correlation Analysis and Prediction of Confirmed Cases of Covid 19 and Meteorological Factor Praditya, Ni Wayan Priscila Yuni; Syaka, Annisa Khodista; Anggraini, Regina
Applied Information System and Management (AISM) Vol. 7 No. 1 (2024): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v7i1.34088

Abstract

The spread and resilience of Covid 19 in an environment depend on meteorological factors. The relationship between the covid case and meteorological factors needs to be examined more deeply. This study aims to determine the relationship between confirmed cases of Covid 19 and meteorological factors, namely temperature and humidity levels. The data used in this study are the number of confirmed cases of Covid 19, the average temperature, and the average humidity level in five states in the United States. Data were obtained from 22 January - 30 September 2020. This study used the Pearson and Spearman Correlation Analysis to find an effect from temperature and humidity levels to increase the number of confirmed cases of Covid 19. The Business Intelligence approach with LSTM is also carried out by predicting a multivariate time series in confirmed cases of Covid 19. Based on the results of Pearson Correlation and Spearman Correlation, it is stated that humidity and temperature have a correlation that affects the spread of Covid 19. The use of multivariate time-series can predict cases of confirmed Covid with meteorological factors such as temperature and humidity levels. The prediction results show that an increase in Covid-19 cases in the States of California, Texas, Florida, Illinois, and Georgia can still occur.