PERBANDINGAN KINERJA ALGORITME C4.5 DAN NAIVE BAYES MENGKLASIFIKASI PENYAKIT DIABETE
Abstract: Diabetes or can be
called with diabetes or blood sugar disease is a disease that is hard to cure
but can be controlled blood sugar levels. This causes people with diabetes is
increasing every year. This study aims to determine which algorithm that has
the best classification accuracy, so that it can be used to assist in
classifying whether a person has diabetes or not. The data used is the Pima
Indians Diabetes dataset obtained from the UCI machine learning. Processing of
data mining is divided into two stages, namely stage of data preprocessing and
feature selection. Results of the research that has been done, C4.5 algorithm
has an accuracy of 73.82% and increased to 74.87%, subsequent to the selection
of attributes. While naïve Bayes has an accuracy rate of 76.30% and increased
to 77.47%. The end result of this research is naïve bayes algorithm is better
than C4.5 algorithms because it has a better accuracy rate
Penulis: Hendra Marcos, Hengky
Setiawan Utomo
Kode Jurnal: jptinformatikadd150855
