Please use this identifier to cite or link to this item: https://repository.uksw.edu//handle/123456789/25493
Title: Penerapan Random Forest untuk Email Spam Filtering
Other Titles: Application of Random Forest Method for Email Spam Filtering
Authors: Anita, Maria
Keywords: Spam;Email;Random forest;Naive bayes;Klasifikasi
Issue Date: 10-May-2022
Abstract: Email merupakan salah satu alat yang penting untuk berkomunikasi, mentransfer file serta dapat digunakan untuk media iklan melalui internet. Penggunaan email semakin meningkat maka banyak pihak yang mengirimkan email dengan pesan yang berisikan virus, penipuan, bahkan pornografi. Email seperti inilah yang disebut spam email dimana email yang tidak diinginkan oleh penerima yang dikirim secara massal. Banyak pengguna email merasa terganggu karena banyaknya waktu yang dihabiskan untuk menghapus satu per satu pesan spam. Dalam penelitian ini dilakukan perbandingan metode klasifikasi Random Forest dan Naïve Bayes untuk melihat metode mana yang paling akurat. Dari hasil pengujian menggunakan confusion matrix diketahui metode random forest memiliki nilai accuracy paling tinggi yaitu 98%, dan Naïve bayes 73%
Email is an important tool for communicating, transferring files and can be used for advertising media over the internet. The use of e-mail is increasing, so many parties send e-mails with messages that contain viruses, fraud, and even pornography. Emails like this are called spam emails where emails that are not wanted by the recipient are sent in bulk. Many email users are annoyed by the amount of time spent deleting individual spam messages. In this study, a comparison of the Random Forest and Naïve Bayes classification methods was carried out to see which method was the most accurate. From the test results using the confusion matrix, it is known that the random forest method has the highest accuracy value, namely 98%, and Naïve Bayes 73%.
URI: https://repository.uksw.edu/handle/123456789/25493
Appears in Collections:T1 - Mathematics

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