HEALTH INSURANCE PREMIUM RISK PREDICTION USING RANDOM FOREST CROSS VALIDATION

Abstract

Health is very important in human life, especially in this pandemic era. This causes many companies to provide insurance services, especially health insurance. The premium is the amount of money that must be paid each month as an obligation given to the insurance company. The premium is determined based on the premium rate and the amount insured. In determining the premium not only based on the premium rate and the amount insured, but it is also necessary to analyze the risk first. In this study, analyze the risk of insurance premiums using data mining methods, forecasting techniques to explore data information. Machine learning, Random Forest algorithm, and selected attributes that have been selected as characteristics of the object to determine the model that produces pattern knowledge. Thus, it can be integrated into the system to predict the amount of health insurance premiums that will be paid each month.