Correlation Analysis of Open Street Map, Demography, and Vaccination on the Number of Covid-19 Cases Using Multiple Linear Regression and Pearson Correlation Product Moment - Aqhbar Habib; Erna Piantari; Lala Septem Riza (Universitas Pendidikan Indonesia, 2024)
At the beginning of 2020, the world was shocked by the spread of Coronavirus Disease 2019 (Covid-19). The resulting losses cover various areas. This research aims to analyze the correlation between spatial data, demographic data, and vaccination data on the spread of Covid-19 in Bandung City using Multiple Linear Regression (MLR) and Pearson Correlation Product Moment (Pearson's r). The results show that there are only 3 variables that are significantly correlated with Covid-19 cases. The lowest variables are Residential, Population Density, and Healthy Homes. Has a significant simultaneous correlation with Covid-19 cases with a coefficient of determination (R^2) of 0.55404. The model built also passed the 3 Classical Assumptions test so that the results can be trusted for their level of truth and feasibility. The results of experiments using the Pearson's r model involving 5 vaccination periods show that out of 30 sub-districts in Bandung City, there are 20 sub-districts that have a significant correlation between vaccination and the addition of Covid-19 cases and have a negative correlation direction of 80.54%. The results of the Pearson's r model experiment involving 6 vaccination periods show that there are 9 sub-districts that have a relationship. With a negative correlation direction of 72.93%.