Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia

Qudsi, Dini Hidayatul and Kartiwi, Mira and Saleh, Nurliyana (2017) Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia. International Journal of Applied Engineering Research, 12 (7). pp. 1334-1339. ISSN 0973-4562 E-ISSN 0973-9769

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Abstract

This study aims to identify the potential benefits that data mining can bring to the health sector, using Indonesian Health Insurance company data as case study. The most commonly data mining technique, decision tree, was used to generate the prediction model by visualizing the tree to perform predictive analysis of chronic diseases. All the steps in data mining process have been performed by a data mining tool, named WEKA. Additionally, WEKA also was utilized to evaluate the prediction performance by measuring the accuracy, the specificity and the sensitivity. Among the result found in this study shows some factors that the health insurance can take into account when predicting the treatment cost of a patient.

Item Type:	Article (Journal)
Additional Information:	6326/57292
Uncontrolled Keywords:	data mining, prediction model, chronic disease, decision tree, sensitivity analysis, WEKA
Subjects:	H Social Sciences > H Social Sciences (General) T Technology > T Technology (General) T Technology > T Technology (General) > T10.5 Communication of technical information T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T58.5 Information technology
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Prof.Ts.Dr Mira Kartiwi
Date Deposited:	20 Jun 2017 15:26
Last Modified:	20 Jun 2017 15:26
URI:	http://irep.iium.edu.my/id/eprint/57292

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