Classification of Different Abdominal Pain using Decision Tree Induction (ID3 Algorithm)

Abstract

Nowadays, data classification techniques are very increasingly and applied in real world domain such as medicine, manufacturing and production, weather prediction, and financial analysis. Data classification is the process of building a model from available data called the training data set and classifying disease according to their attributes. Among the increase in the use of data classification technique, decision tree induction method is one of the most useful method. In this system, presents the classification of acute abdominal pain problems using decision tree induction. Thus, this system intends to provide information for junior medical practitioners and the user who faced abdominal pain. This paper implements the decision tree using ID3 and gives advice to users about the cases acute abdominal pain. This paper calculates the system accuracy by using holdout method and implemented by Java programming language. Jdk1.6 and SQL server 2008.