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Elfaladonna, Febie
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Computer Science & IT

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ANALISA METODE CLASSIFICATION-DECISSION TREE DAN ALGORITMA C.45 UNTUK MEMPREDIKSI PENYAKIT DIABETES DENGAN MENGGUNAKAN APLIKASI RAPID MINER Elfaladonna, Febie; Rahmadani, Ayu
SINTECH (Science and Information Technology) Journal Vol 2 No 1 (2019): SINTECH Journal Edisi April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (356.414 KB) | DOI: 10.31598/sintechjournal.v2i1.293

Abstract

Diabetes disease is a degenerative disease that each year the presentation of its victims are always increasing. Ignorance of lay people to predict the likelihood of the disease either from a derivative or derivatives is still not a bit. These things affect the level of vigilance sufferers against things that can trigger diabetes getting worse. Classification of research aims to form model decision tree in order for handling derivative-based diabetes disease are increasingly easy to do. To generate new information then used calculation algorithm c. 45 and testing algorithms that use application rapid miner would further reinforce the decision. The research on testing using multiple attribute classification i.e. the attribute weight, gender, blood pressure, blood sugar levels, and a history of diabetes. All of these attributes will be used as reference in search results so that sufferers can predict whether diabetes is the diabetes disease suffered a derivative or derivatives not
Co-Authors Rahmadani, Ayu