Bayesian Belief Network untuk Menghasilkan Fuzzy Association Rules  

Oleh:

Intan, Rolly ; Yuliana, Oviliani Yenty ; Kristanto, Dwi

Jenis: Article from Journal - ilmiah nasional - terakreditasi DIKTI - non-atma jaya
Dalam koleksi: Jurnal Teknik Industri vol. 12 no. 1 (Jun. 2010), page 55-60.
Topik: Medical Record; Mutual Information; Conditional Probability; Bayesian Belief Network; Fuzzy Association Rules
Fulltext: 17946-20284-1-PB.pdf (197.14KB)

Isi artikel

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.

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