Penyaringan Spam email menggunakan K-Means

Abstract

Abstract - In Indonesia, there are many cases of misuse of email that harm others. Emails that are known as junk emails contain phishing, scams, malware and even advertisements. This study aims to sort out spam and ham emails using K-Means Clustering as an effort to reduce the amount of spam. K-means can divide based on the cluster created. From the results of optimization research using K-Means Clustering produces 100% accuracy. So based on the accuracy value obtained, the clustering frequency distribution and K-Means can be used to optimize spam sorting in emails..
Keywords: Spam email, K-Means, Preprocessing, machine learning.