The pet health cost model using multiple linear regression to determine pet health insurance.

The COVID-19 pandemic that has hit the world has brought a positive trend to the pet industry in Indonesia. However, this increase in the number of pet owners is not accompanied by a strong commitment. As a result, not a few pets are abandoned because the owner is not able to cope with the soaring spike in health costs. In America, this phenomenon has been proven to be successfully prevented by the existence of animal health insurance, which gives pet owners a feeling of security if something bad threatens the health of their pets. However, pet health insurance in Indonesia is still relatively new even though Indonesia also has a large market share, which is around 70% of the Indonesian population. Therefore, this study will use multiple linear regression and utilize the bootstrapping technique to build a model of pet health costs that is used to determine premiums for pet health insurance. The results showed that the variables of the pet's age, the condition of the pet having been sterilized, routine control by the vet, and the level of activity of the animal had a significant effect on the model. Based on the model that has been successfully formed, the average frequency of visits to the veterinarian and the average amount of expenses incurred in a year are obtained, so that the prediction of the premium amount is IDR 1,003,794 annually. [ABSTRACT FROM AUTHOR]