Email Spam Classification Using Data Mining Techniques

Abstract

Today the communication by electronic mail (e-mail) is another channel that has been popular because it is simple, easy to use, fast and free of charge. This is why it is the way that others use to send e-mail spam, for the purpose of advertising or deception. This article presents a study comparison the performance of electronic mail classification with data mining technique such as Decision  tree Naive Bayes and K-Nearest Neighbor. The results of this research found naive bayes algorithm provides the highest accuracy of 92.48%.