IMPLEMENTASI FUZZY DECISION TREE UNTUK MENDIAGNOSA PENYAKIT HEPATITIS
Abstract: The objectives of
this research are (1) To apply one of the classification techniques, namely
Fuzzy ID3 Decision Tree on the data examination patient lab results; (2) To
know the results of the implementation of Fuzzy ID3 lab results patient data
using MySQL PHP application that has been designed. The method used in this
research is the method of classification by fuzzy decision tree. By applying
data mining techniques on the data expected to be found hepatitis classification
rules that can be used to predict a person's potential disease hepatitis. The
algorithm used in the fuzzy decision tree is ID3. Results Implementation of
Fuzzy ID3 against hepatitis B the data are as follows: (a) it determines the
fuzzy rules for the third training set; (b) calculation of the training set
third best accuracy is obtained with a value of 88.5% where data used 15
training data sets; (c) Establishment of Fuzzy ID3 influence on the outcome of
the training set. The more and more accurate data will increase the accuracy of
the results of Fuzzy ID3.
Penulis: Jefry Latu Handarko, Alamsyah
Alamsyah
Kode Jurnal: jpmatematikadd150803
