Fuzzy Decision Tree dengan Algoritme ID3 pada Data Diabetes

Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/76357

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DC Field	Value	Language
dc.contributor.author	F. Romansyah
dc.contributor.author	I. S. Sitanggang
dc.contributor.author	S. Nurdiati
dc.date.accessioned	2015-09-29T03:38:10Z
dc.date.available	2015-09-29T03:38:10Z
dc.date.issued	2009
dc.identifier.issn	1942-9703	-
dc.identifier.uri	http://repository.ipb.ac.id/handle/123456789/76357
dc.description.abstract	Decision tree is one of widely used methods in developing classification models, In Order to handle uncertainty, fuzzy approach is used. This work applied a classification technique using fuzzy decission tree method on diabetes dataset to obtasin classification rules for predicting new data. Fuzzy ID3 (fuzzy Iterative Dichotomiser 3) was used to develop fuzzy tree with the bighest accurasy 94,15 % for fuzziness control threshold ....	en
dc.language.iso	id
dc.title	Fuzzy Decision Tree dengan Algoritme ID3 pada Data Diabetes	en
Appears in Collections:	Faculty of Mathematics and Natural Sciences

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