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Please use this identifier to cite or link to this item: https://repository.uksw.edu/handle/123456789/3267
Title: Implementasi Naïve Bayesian Classifier Untuk Kasus Filtering SMS Spam
Authors: Selo W.T., Gilang Jalu
Susanto, Budi
Delima, Rosa
Keywords: Naïve Bayesian;spam;SMS;feature selection
Issue Date: Feb-2013
Publisher: Tata Usaha Fakultas Teknologi Informasi Universitas Kristen Satya Wacana Salatiga
Abstract: 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.
Description: Aiti : Jurnal Teknologi Informasi. Vol. 10, no. 1, Februari 2013., p.62 – 70
URI: http://repository.uksw.edu/handle/123456789/3267
ISSN: 1693-8348
Appears in Collections:Aiti 2013 Vol. 10, No. 1, Februari



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