PERAMALAN PENDERITA DIABETES MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR

andi syafar

doi:10.31850/jsilog.v1i2.1120

andi syafar UIN Alauddin

DOI: https://doi.org/10.31850/jsilog.v1i2.1120

Keywords: diabetes prediction, knn, cross validation

Abstract

Diabetes is a metabolic disorder caused by the pancreas not producing enough insulin. Pima Indian Dataset is to predict diagnostically whether a patient is potential or unpotential diabetes. .All data taken in this dataset are women at least 21 years of age from the Pima Indians. For the parameters, we took several parameters such as blood pressure, triceps skin thickness, history of diabetes, and others. The existing data is then processed using Rapidminer tools using cross validation parameters 2,3, and 5. After testing, we get the results that the higher the cross validation value, the lower the accuracy. Even if we look at the K-1 sample, the accuracy value has no effect on cross validation.

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