Fuzzy Based Decision Support Model for Health Insurance Claim

Insurance industry in Indonesia has shown promising result based on premium growth 2014-2018, as recorded General Market Update 2019. With the increase of premium, claim rate also grows. companies face challenges processing claims. Many factors need to be carefully considered before making a decision. This paper proposes decision support model (DSM) score cases and propose risk category (CRC) (CD). The was built with 13 parameters, divided into non-fuzzy group fuzzy group. analytic hierarchy process (AHP) method used determine priority weight (PW) among parameters. Tsukamoto’s logic (FL) applied A simple mathematics (SMM) exercised calculate aggregate (CRS). Finally, CRC CD were derived from CRS using rule base. tested 19611 actual history records. was: 6171 (31.47%) accepted CRC= low, 3459 (17.64%) pending (CRC medium), 9981 (50.89%) high). DSM implemented python Google COLAB Datapane create various graphics.