PREDIKSI EMAIL PHISING MENGGUNAKAN SUPPORT VECTOR MACHINE

Chaerul Umam, L. Budi Handoko

Abstract


Email phising merupakan salah satu bentuk kejahatan di internet yang dapat merugikan banyak orang. Ketika seseorang sudah terkena phising maka data data orang tersebut dapat hilang dan digunakan oleh orang yang tidak bertanggung jawab. Pada penelitian ini, akan melakukan proses klasiifkasi email phising dengan menggunakan bantuan machine learning yaitu algoritma SVM. Dataset yang digunakan pada penelitian ini yaiitu merupakan dataset yang berisi body email yang terdiri dari total 18650 data yang terdiri dari 11322 data safe email dan 7328 data phising email. Dari data tersebut, akan dibagi menjadi 70% data pelatihan dan 30% data pengujian. Setelah dilakukan proses pengujian pada penelitian ini, algoritma SVM yang digunakan mendapatkan akurasi pengujian sebesar 84.56%.


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References


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DOI: https://doi.org/10.30998/semnasristek.v8i01.7138

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