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

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...

Full description

Bibliographic Details
Main Authors:	Qudsi, Dini Hidayatul, Kartiwi, Mira, Saleh, Nurliyana
Format:	Article
Language:	English English
Published:	Research India Publication 2017
Subjects:	H Social Sciences (General) T Technology (General) T10.5 Communication of technical information T58.5 Information technology
Online Access:	http://irep.iium.edu.my/57292/ http://irep.iium.edu.my/57292/ http://irep.iium.edu.my/57292/1/ijaerv12n7_34.pdf http://irep.iium.edu.my/57292/2/57292-Predictive%20Data%20Mining%20of%20Chronic%20Diseases%20Using%20Decision%20Tree_SCOPUS.pdf

id	iium-57292
recordtype	eprints
spelling	iium-572922017-06-20T07:26:07Z http://irep.iium.edu.my/57292/ Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia Qudsi, Dini Hidayatul Kartiwi, Mira Saleh, Nurliyana H Social Sciences (General) T Technology (General) T10.5 Communication of technical information T58.5 Information technology 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. Research India Publication 2017 Article PeerReviewed application/pdf en http://irep.iium.edu.my/57292/1/ijaerv12n7_34.pdf application/pdf en http://irep.iium.edu.my/57292/2/57292-Predictive%20Data%20Mining%20of%20Chronic%20Diseases%20Using%20Decision%20Tree_SCOPUS.pdf 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 https://www.ripublication.com/ijaer17/ijaerv12n7_34.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	H Social Sciences (General) T Technology (General) T10.5 Communication of technical information T58.5 Information technology
spellingShingle	H Social Sciences (General) T Technology (General) T10.5 Communication of technical information T58.5 Information technology Qudsi, Dini Hidayatul Kartiwi, Mira Saleh, Nurliyana Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia
description	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.
format	Article
author	Qudsi, Dini Hidayatul Kartiwi, Mira Saleh, Nurliyana
author_facet	Qudsi, Dini Hidayatul Kartiwi, Mira Saleh, Nurliyana
author_sort	Qudsi, Dini Hidayatul
title	Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia
title_short	Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia
title_full	Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia
title_fullStr	Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia
title_full_unstemmed	Predictive data mining of chronic diseases using decision tree: A case study of health insurance company in Indonesia
title_sort	predictive data mining of chronic diseases using decision tree: a case study of health insurance company in indonesia
publisher	Research India Publication
publishDate	2017
url	http://irep.iium.edu.my/57292/ http://irep.iium.edu.my/57292/ http://irep.iium.edu.my/57292/1/ijaerv12n7_34.pdf http://irep.iium.edu.my/57292/2/57292-Predictive%20Data%20Mining%20of%20Chronic%20Diseases%20Using%20Decision%20Tree_SCOPUS.pdf
first_indexed	2023-09-18T21:20:57Z
last_indexed	2023-09-18T21:20:57Z
_version_	1777411878247464960

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

Similar Items