Willingness to Pay of Fishermen Insurance Using Logistic Regression with Parameter Estimated by Maximum Likelihood Estimation Based on Newton Raphson Iteration

Abstract

The high risk of losing fishermen's life while at sea is inversely proportional to their low welfare. Fishermen are also unable to meet their daily needs when they are not going to sea. Fishermen welfare insurance can be a solution for them to meet their daily needs. Willingness to Pay (WTP) of fishermen to participate in fishermen welfare insurance can be analyzed using Logistic Regression with Newton Raphson and Genetic Algorithm approximations. Some of the main factors that can support their WTP to participate in fishermen welfare insurance, are fishermen education, membership in the fishing community, membership in fisherman business cards, and knowledge about the existence of fishermen insurance. From these four factors, Logistic Regression Model is generated which is expected to help the increase of fishermen’s WTP on fishermen insurance in Indonesia.