Jurnal Pilar Nusa Mandiri
Vol 15 No 2 (2019): PILAR Periode September 2019

KLASIFIKASI SMS SPAM MENGGUNAKAN SUPPORT VECTOR MACHINE

Agus Setiyono (STMIK Nusa Mandiri)
Hilman F Pardede (Pusat Penelitian Infomatika LIPI & STMIK Nusa Mandiri)

Article Info

Publish Date
08 Sep 2019

Abstract

It is now common for a cellphone to receive spam messages. Great number of received messages making it difficult for human to classify those messages to Spam or no Spam. One way to overcome this problem is to use Data Mining for automatic classifications. In this paper, we investigate various data mining techniques, named Support Vector Machine, Multinomial Naïve Bayes and Decision Tree for automatic spam detection. Our experimental results show that Support Vector Machine algorithm is the best algorithm over three evaluated algorithms. Support Vector Machine achieves 98.33%, while Multinomial Naïve Bayes achieves 98.13% and Decision Tree is at 97.10 % accuracy.

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Journal Info
Jurnal Pilar Nusa Mandiri
Website

Abbrev

pilar

Publisher

STMIK Nusa Mandiri

Subject

Computer Science & IT

Description

Jurnal Pilar merupakan jurnal ilmiah yang diterbitkan oleh program studi sistem informasi STMIK Nusa Mandiri. Jurnal ini berisi tentang karya ilmiah yang bertemakan: Rekayasa Perangkat Lunak, Sistem Pakar, Sistem Penunjang, Keputusan, Perancangan Sistem Informasi, Data Mining, Pengolahan ...