Generating the Classification Rule Using Decision Tree Algorithm

Abstract

Data mining has been used very frequently to extract hidden information from large databases. The classification rule generation process is based on the decision tree as a classification method where the generated rules are studied. This technique is forms of data analysis that can be used extract models to describe important data class. The main purpose of the classification system is to induce rules and accuracy that describe decision tree. In this paper, there are two mains phases. In the training phase, attributes are analyzed by C4.5 algorithm. By using the training data, this system will construct the model or classifier to generate the form of classification rules. In the testing phase, compare the input test data and the classification rules to obtain the result. This system can apply to implement the classification system for IT Technicians job roles.