ANALISA DATA MINING UNTUK PREDIKSI PENYAKIT HEPATITIS DENGAN MENGGUNAKAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE - Eka Wulansari Fridayanthie (Jurnal Khatulistiwa Informatika, 2015)
In the case of hepatitis disease prediction has been solved by a method using Support Vector Machine (SVM) .Penyakit hepatitis is an inflammatory disease of the liver due to viral infection that attacks and cause damage to cells and organs function hati.Penyakit forerunner hepatitis is a disease of the liver cancer. Attributes or variables that have as many as 20 attributes which consists of 19 attributes preditor and 1 as the output destination attribute used to differentiate the results of the examination. Invene dataset from the University of California (UCI) Machine Learning Repository 583 as the data used and replace missing after the data is used only to evaluate the data 153 SVMyang approach proposed in the study ini.Hasil simulations showed that by developing this model achieved a reduction in dimensions and identification hati.Salah cancer of the optimization algorithm is quite popular is Naïve Bayes. In this study, will be used also classification algorithm Support Vector Machine (SVM) will be used to establish a predictive classification model of hepatitis.Keywords: Hepatitis,Naïve Bayes , Support Vector Machine