IMPLEMENTASI FUZZY DECISION TREE UNTUK MENDIAGNOSA PENYAKIT HEPATITIS - Handarko, Jefry Latu; Alamsyah, Alamsyah (Unnes Journal of Mathematics, 2015)
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.