Jurnal Teknik Industri
Vol. 12 No. 1 (2010): JUNE 2010

Bayesian Belief Network untuk Menghasilkan Fuzzy Association Rules

Rolly Intan (Fakultas Teknologi Industri, Jurusan Teknik Informatika, Universitas Kristen Petra)
Oviliani Yenty Yuliana (Fakultas Teknologi Industri, Jurusan Teknik Informatika, Universitas Kristen Petra)
Dwi Kristanto (Fakultas Teknologi Industri, Jurusan Teknik Informatika, Universitas Kristen Petra)



Article Info

Publish Date
19 May 2010

Abstract

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.

Copyrights © 2010






Journal Info

Abbrev

ind

Publisher

Subject

Industrial & Manufacturing Engineering

Description

Jurnal Teknik Industri aims to: Promote a comprehensive approach to the application of industrial engineering in industries as well as incorporating viewpoints of different disciplines in industrial engineering. Strengthen academic exchange with other institutions. Encourage scientist, practicing ...