Fadri, Wahyugi
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Klasifikasi Penyakit Hati dengan Menggunakan Metode Naive Bayes Fadri, Wahyugi
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v5i1.230

Abstract

Data mining is the process of finding relationships in data that are not known to the user and understandably presenting them so that these relationships can form the basis of decision-making. The purpose of this study was to design a data mining website using the Naive Bayes method to classify liver disease symptoms and to test a data mining website using the Naive Bayes method to assist in classifying liver disease. The data was processed by 50 medical records of liver disease in Lubuk Basung Hospital which consisted of symptoms and diseases. The method used is the Naive Bayes method which has a fairly high accuracy value. one method that can be used to classify data. Bayesian classification is a statistical classifier that can be used to predict the probability of belonging to a class. Then it was developed into a website-based form using the PHP Framework Codeigniter programming language and MySQL as the database. The system to be built is based on the Naive Bayes method which is one of the Data Mining methods. The test results from 50 medical record data of patients with liver disease, by applying the Naive Bayes method which is applied to data mining, is useful for comparing hospital data with system data. From 45 training data and 5 testing data, the accuracy rate is 60%.