IMPLEMENTASI NAÏVE BAYESIAN CLASSIFIER UNTUK KASUS FILTERING SMS SPAM - Gilang Jalu Selo W.T.; Budi Susanto (Universitas Kristen Duta Wacana, 2014)
In 2011, the circulation of SMS spam in Indonesia was rampant. The SMS can contain promotion of a product which is often unsolicited by the recipient or fraud. This is an overlooked issue in Indonesia. But spam has been a very common topic in other countries. To resolve these problems, we need a system that can recognize SMS spam so the SMS can be diverted or marked prior to the user. In this research, we built a system that implementing the Naive Bayesian classifier for classifying SMS spam, so the user can recognize the SMS spam. The result of this research, the system built is able to classify a SMS into categories spam and not spam. Naïve Bayesian classifier can be implemented effectively in the case of SMS spam filtering. The proper use of text preprocessing can improve the performance of this classification system.