Abstract:
The issue of health insurance costs has become a major concern in the healthcare system
in the USA. Determining the accurate health insurance cost is crucial for individuals and
families who rely on health insurance for financing their healthcare. This research aims
to compare the most effective methods for determining health insurance costs using
variable selection methods in multiple linear regression models. The variable selection
methods used are forward selection and backward elimination. Based on the application
in the regression model, the forward selection method yielded dan RMSE values of
79.68% and 2024.295, respectively. The backward elimination method produced dan
RMSE values of 96.77% and 807.175, respectively. The most effective variable
selection method for determining health insurance costs in this case is backward
elimination.
