Rolly Intan
Fakultas Teknologi Industri, Jurusan Teknik Informatika, Universitas Kristen Petra

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Bayesian Belief Network untuk Menghasilkan Fuzzy Association Rules Rolly Intan; Oviliani Yenty Yuliana; Dwi Kristanto
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 12 No. 1 (2010): JUNE 2010
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (201.875 KB) | DOI: 10.9744/jti.12.1.55-60

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.