Employee Likelihood of Purchasing Health Insurance using Fuzzy Inference System

Abd Rahman, Mohd Nordin (2012) Employee Likelihood of Purchasing Health Insurance using Fuzzy Inference System. International Journal of Computer Science Issues, 9 (1). pp. 112-116. ISSN 1694-0814

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Many believe that employees’ health and economic factors plays an important role in their likelihood to purchase health insurance. However decision to purchase health insurance is not trivial matters as many risk factors that influence decision. This paper presents a decision model using fuzzy inference system to identify the likelihoods of purchasing health insurance based on the selected risk factors. To build the likelihoods, data from one hundred and twenty eight employees at five organizations under the purview of Kota Star Municipality Malaysia were collected to provide input data. Three risk factors were considered as the input of the system including age, salary and risk of having illness. The likelihoods of purchasing health insurance was the output of the system and defined in three linguistic terms of ‘Low’, ‘Medium’ and ‘High’. Input and output data were governed by the Mamdani inference rules of the system to decide the best linguistic term. The linguistic terms that describe the likelihoods of purchasing health insurance were identified by the system based on the three risk factors. It is found that twenty seven employees were likely to purchase health insurance at ‘Low’ level and fifty six employees show their likelihoods at ‘High’ level. The usage of fuzzy inference system would offer possible justifications to set a new approach in identifying prospective health insurance purchasers.

Item Type: Article
Keywords: Health Insurance, Fuzzy rule, Risk factor, Fuzzy logic, Likelihoods
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Institute: Faculty of Informatics & Computing
Depositing User: Dr Mohd Nordin Abdul Rahman
Date Deposited: 20 May 2014 02:40
Last Modified: 20 May 2014 02:40
URI: http://erep.unisza.edu.my/id/eprint/1158

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