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dc.contributor.authorF. Romansyah
dc.contributor.authorI. S. Sitanggang
dc.contributor.authorS. Nurdiati
dc.date.accessioned2015-09-29T03:38:10Z
dc.date.available2015-09-29T03:38:10Z
dc.date.issued2009
dc.identifier.issn1942-9703
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/76357
dc.description.abstractDecision 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.isoid
dc.titleFuzzy Decision Tree dengan Algoritme ID3 pada Data Diabetesen


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