Bayesian Belief Network untuk Menghasilkan Fuzzy Association Rules

Bayesian Belief Network (BBN), one of the data mining classification methods, is used in this research for mining and analyzing medical track record from a relational data table. In this paper, a mutual information concept is extended using fuzzy labels for determining the relation between two fuzzy...

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Bibliographic Details
Main Authors: Rolly Intan, Oviliani Yenty Yuliana, Dwi Kristanto
Format: Article
Language:English
Published: Petra Christian University 2010-01-01
Series:Jurnal Teknik Industri
Subjects:
Online Access:http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/17946
Description
Summary:Bayesian Belief Network (BBN), one of the data mining classification methods, is used in this research for mining and analyzing medical track record from a relational data table. In this paper, a mutual information concept is extended using fuzzy labels for determining the relation between two fuzzy nodes. The highest fuzzy information gain is used for mining fuzzy association rules in order to extend a BBN. Meaningful fuzzy labels can be defined for each domain data. For example, fuzzy labels of secondary disease and complication disease are defined for a disease classification. The implemented of the extended BBN in a application program gives a contribution for analyzing medical track record based on BBN graph and conditional probability tables.
ISSN:1411-2485