Analisis Premi Asuransi Jiwa Menggunakan Model Cox Proportional Hazard

Indonesian Journal of Applied Statistics Pub Date : 2019-03-13 DOI:10.13057/IJAS.V1I2.25280

Firda Anisa Fajarini, Mohamat Fatekurohman

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引用次数: 1

Abstract

Cox proportional hazard model is a regression model that is used to see the factors that cause an event. The survival analysis used in this research is the period of time the client is able to pay the life insurance premium using Cox proportional hazard model with Breslow method.The purpose of this research is to know how sex, age, insured money, job, method of payment of premium, premium, and type of product can influence the level of ability of client to make payment of life insurance premium based on customer data from PT. BRI Life Insurance Branch of Jember in 2007.The result of this research is the final model of Cox proportional hazard obtained from several variables which have significant influence with simultaneous and partial significance test is the variable of insured money (X₃), variable of payment method of premium (X₅), premium variable (X₆) , and insurance product variable (X₇) . The four variables are said to have a significant effect on the model, so that the final model of Cox proportional hazard is obtained that consists of the parameter estimation (β) value of each variable

Keywords : survival analysis; cox proportional hazard model; breslow method; life insurance.

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Cox比例风险模型是一种回归模型，用于查看导致事件的因素。本研究使用的生存分析是客户能够支付人寿保险费的时间，使用Cox比例风险模型和Breslow方法。本研究以2007年11月PT. BRI人寿保险分公司的客户数据为基础，探讨性别、年龄、投保金额、工作、保费支付方式、保费及产品种类对客户缴纳寿险保费能力的影响。本研究的结果是通过同时显著性检验和部分显著性检验得出的Cox比例风险的最终模型，这些变量分别是投保金额变量(X3)、保费支付方式变量(X5)、保费变量(X6)和保险产品变量(X7)。认为这4个变量对模型有显著影响，从而得到由各变量参数估计(β)值组成的Cox比例风险最终模型。关键词:生存分析;Cox比例风险模型;‘方法;人寿保险。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Indonesian Journal of Applied Statistics

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