Penerapan Data Standardization dan Multilayer Perceptron pada Identifikasi Website Phishing

YUSUP MIFTAHUDDIN; MOHAMAD MUQIIT FATURRAHMAN

doi:10.26760/mindjournal.v7i2.111-123

Penerapan Data Standardization dan Multilayer Perceptron pada Identifikasi Website Phishing

YUSUP MIFTAHUDDIN, MOHAMAD MUQIIT FATURRAHMAN

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Abstrak

Website phishing adalah salah satu masalah utama dalam bidang keamanan website. Website phishing dibuat oleh orang yang tidak bertanggungjawab untuk mengambil informasi pribadi seseorang contohnya seorang hacker atau cracker. Teknik umum yang digunakan pada phishing yaitu manipulasi Uniform Resource Locator (URL), pemalsuan halaman situs web, dan pop up window. Pada tahun 2019, APWG (Anti-Phishing Working Group) mendeteksi kasus phishing sebanyak 162.155 kasus di dunia. Pada penelitian ini, melakukan eksperimen dengan menerapkan metode Data Standardization dan Multilayer Perceptron (MLP) untuk mendeteksi website phishing. Eksperimen dilakukan menggunakan 2 model yaitu model A dan model B. Untuk melihat performa dari model MLP yang dihasilkan dapat dilihat menggunakan tingkat accuracy, recall, precision, f1-score dan specificity. Selain itu juga dapat dilihat menggunakan confusion matrix untuk melihat kinerja pada model MLP. Pada penelitian ini menghasilkan bahwa model B merupakan model terbaik dengan mendapatkan tingkat accuracy 95.7% , recall 97.3%, precision 94.0%, f1-score 95.6% dan specificity 97.3%.

Kata kunci: multilayer perceptron, data standardization, website phishing

Abstract

Phishing websites are one of the main problems in the field of website security. Phishing websites are created by people who are not responsible for taking someone's personal information. Common techniques used in phishing are Uniform Resource Locator (URL) manipulation, website page spoofing, and pop up windows. In 2019, APWG (Anti-Phishing Working Group) detected 162,155 cases of phishing in the world. In this study, conducting experiments by using Data Standardization and Multilayer Perceptron (MLP) methods to detect phishing websites. Experiments were carried out using 2 models, namely model A and B. To see the performance of MLP model, it can be seen using score of accuracy, recall, precision, f1-score and specificity. In addition, it can also be seen using the confusion matrix to see the performance of the MLP model. This research shows that model B is the best model with 95.7% accuracy, 97.3% recall, 94.0% precision, 95.6% f1-score and 97.3% specificity.

Keywords: multilayer perceptron, data standardization, website phishing

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Referensi

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DOI: https://doi.org/10.26760/mindjournal.v7i2.111-123