Library Automation and Digital Archive
LONTAR
Fakultas Ilmu Komputer
Universitas Indonesia

Pencarian Sederhana

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Call Number SEM-356
Collection Type Indeks Artikel prosiding/Sem
Title Penerapan Data Minning Dalam Email Filtering Menggunakan Metode Naive Bayesian
Author E . Didik Madyatmadja , Yuni Ramadhini , David JM Sembiring;
Publisher Prosiding medan,25-26 februari 2011 konferensi nasional sistem informasi 20011 information system: bridging gap between theories and practices (KNSI)
Subject
Location
Lokasi : Perpustakaan Fakultas Ilmu Komputer
Nomor Panggil ID Koleksi Status
SEM-356 TERSEDIA
Tidak ada review pada koleksi ini: 44741
Spam mail is an email which continuing from thousand of email users and usually contain of product/services/business promotion,pornography,virus and unnecessary emails. Until now, spam mail issues keep blooming by the develipong software as well, email filtering using variant of methods such as naïve Bayesian classification , address block,association rules and other methods. From lost of email filtering methods, seems naïve Bayesian has more accurateness level. In this final exam, writer would like to explain the naïve Bayesian classification method of email filtering. Naïve Bayesian filter was developed by bunch of email which had been classified into spam mail and legitimate. By learning process, the email filtering expected to be more accurate. Keywords : email filtering , Bayesian filter , naïve bayes , spam email, legitimate mail.