KLASIFIKASI EMAIL SPAM MENGGUNAKAN ALGORITMA ARTIFICIAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE

Abstract

Electronic mail (email) is one of the most frequently used communication tools today. However, the popularity of email also brings problems, one of which is the rise of spam email. Spam emails are not only annoying but can also have a bad impact on someone. Therefore, this research was carried out with the aim of providing a solution to this problem, namely a machine learning model that can classify spam emails. This research applies supervised learning using artificial neural network (ANN) and support vector machine (SVM) algorithms and uses spam email data as an experiment. The comparison of the two algorithms is carried out by observing the evaluation metrics resulting from the experiments. The results obtained from the experiment are that the ANN algorithm has better performance than the SVM algorithm, which can be seen from the comparison of the evaluation metrics of the two algorithms, where the ANN algorithm has a higher score in all aspects. So, the ANN algorithm can be a good algorithm for building a model that can detect the presence of spam emails.