ANALISIS PENYARINGAN EMAIL SPAM MENGGUNAKAN METODE NAIVE BAYES - Elsya Moriesta; Selviani Selviani; Ali Ibrahim (Annual Research Seminar (ARS), 2017)
Email is one of the most important entities in terms of communication, whether personal, corporate, government and other communities. Widespread use of email as a medium of communication has a negative impact. One of the negative impacts that resulted is that many unwanted emails enter in the inbox. This condition is commonly known as spam. The presence of spam in emails led to research on spam filter software development to classify spam and non-spam emails automatically. Naïve Bayes is a function widely used by spam filter developers as a function to classify email because it is simple and easy to implement. To improve the accuracy and speed up the computing process it is necessary to perform several stages. There are three stages to build Bayesian filters: building spam database, Bayesian filter training, and filtering.