Sistem Deteksi Surel SPAM Dengan DNSBL Dan Support Vector Machine Pada Penyedia Layanan Mail Marketing - Fahri Firdausillah; Muhammad Hafidz; Erika Devi Udayanti; Etika Kartikadarma (Forum Kerjasama Pendidikan Tinggi (FKPT), 2022)
Mail marketing is an effective communication medium for users and internet providers. Many companies use email as a mean of communication with customers to ensure customers are not left behind with the latest information, and at once provide personalized offers to specific customers. However, not all emails that are sent reach mail inbox as expected. There are several factors as the cause including content that does not comply with the writing rules and tends to have SPAM signatures, invalid e-mail addresses, the sender domains are registered in the blacklist and so forth. Mail marketing service providers such as MTarget and Mailchimp must ensure that emails sent by their customers have no potential to become spam, because it can affect all of their mail marketing services will be blacklisted, thus promotional goals will not be achieved. In that case, a system is needed to check the e-mail that will be sent by the customer, to ensure that the e-mail will not detected as a spam by email service applications such as Gmail. This research produces an email validator system that can prevent sending emails that have the potential to become SPAM, so as to reduce the risk of a mail marketing service provider being blacklisted which results in delays in promotion via email and a decrease in marketing turnover. The proposed method used in this research is the Domain Name System-Based Blackhole List (DNSBL) to check the IP and the sending domain and the Support Vector Machine (SVM) to check the content of the email to be sent. The system developed has been functioning as expected and has an accuracy rate of 97.54% in detecting SPAM emails.