TAMIMY, MUHAMMAD ZAKI and Samsuryadi, Samsuryadi and Saputra, Danny Matthew (2018) PERBANDINGAN ANTARA NAIVE BAYES DAN SINGLELAYER PERCEPTRON UNTUK PENDETEKSIAN SPAM EMAIL. Undergraduate thesis, Sriwijaya University.
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Abstract
Spam issues in e-mails need to be addressed so as not to interfere with e-mail user convenience. The most common method for detection of anti-spam works by separating or grouping the contents of the email and then studying a number of spam emails that have been detected. The spam email detection method used by the Naïve Bayes Classifier (NB) and Single-Layer Perceptron Classifier (SLP) respectively have resulted in accuracy performance of 88,75% and 81,25. The NB method is 7,50% higher than the SLP method for spam detection.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Naïve Bayes Classifier, Spam Email, Single-Layer Classifier. |
Subjects: | R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics |
Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
Depositing User: | Mrs Sri Astuti |
Date Deposited: | 30 Sep 2019 01:47 |
Last Modified: | 30 Sep 2019 01:47 |
URI: | http://repository.unsri.ac.id/id/eprint/9527 |
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