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All Journal International Journal of Electrical and Computer Engineering Journal of Information Technology and Computer Science JIPF (Jurnal Ilmu Pendidikan Fisika) Jurnal INSYPRO (Information System and Processing) Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat JURNAL IT: Media Infromasi STMIK Handayani Makassar EPI International Journal of Engineering Jurnal Penelitian Enjiniring Fakultas Teknik Unhas Indonesian Journal of Electrical Engineering and Computer Science PINISI Discretion Review Jurnal Pengabdian Mandiri J-ENSITEC (Journal of Engineering and Sustainable Technology) Jurnal Sistem Informasi Journal of Information Technology and its Utilization
Muhammad Niswar
Departemen Teknik Informatika, Fakultas Teknik, Universitas Hasanuddin
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Physics Public Health Social Sciences Other

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WEBSITE PHISING DETECTION APPLICATION USING SUPPORT VECTOR MACHINE (SVM) Diki Wahyudi; Muhammad Niswar; A. Ais Prayogi Alimuddin
Journal of Information Technology and Its Utilization Vol 5 No 1 (2022)
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.1.4836

Abstract

Phishing is an act to get someone's important information in the form of usernames, passwords, and other sensitive information by providing fake websites that are similar to the original. Phishing (fishing for important information) is a form of criminal act that intends to obtain confidential information from someone, such as usernames, passwords and credit cards, by impersonating a trusted person or business in an official electronic communication, such as electronic mail or instant messages. Along with the development of the use of electronic media, which is followed by the increase in cyber crime, such as this phishing attack. Therefore, to minimize phishing attacks, a system is needed that can detect these attacks. Machine Learning is one method that can be used to create a system that can detect phishing. The data used in this research is 11055 website data, which is divided into two classes, namely "legitimate" and "phishing". This data is then divided using 10-fold cross validation. While the algorithm used is the Support Vector Machine (SVM) algorithm which is compared with the decision tree and k-nearest neighbor algorithms by optimizing the parameters for each algorithm. From the test results in this study, the best system accuracy was 85.71% using SVM kernel polynomial with values of degree 9 and C 2.5.
Co-Authors ', Wardi A. Ais Prayogi Alimuddin A.Ais Prayogi Abdul Rahman Djamaluddin Achmad Bakri Muhiddin Achmad Basuki Adnan - Adnan Adnan Adnan Adnan Ady W Paundu Ady Wahyudi P Ady Wahyudi Paundu Ahmad Ilham, Amil Ais P Alimuddin Amil A Ilham Amil A. Ilham Amil Ahmad Ilham Andani Andani Achmad Andi Armyn Nurdin, Andi Armyn Andrisasmita Rachmat Anugrayani Bustamin Aswad, Iqra Aulia Darnilasari Azis, Masyitha Baharuddin Hamzah Christoforus Yohanes Diki Wahyudi Elly Warni Fachrurrozie Haris, Muhammad Ahlan Firmansyah J Kusuma Furqan Zakiyabarsi Ida R Sahali Idar Mappangara Indrabayu Indrabayu Ingrid Nurtanio Intan Sari Areni Iqra Aswad Iqra Aswad M Alief F Imran Marindah Wardhani, Tyanita Puti Muh. Alief Fahdal Imran Oemar Muhammad Awaluddin, Muhammad Muhammad Irsan Sabir Muhammad Nur Muhammad Nur Mukarramah Yusuf Novy NRA Mokobombang Nurhasanah Nurhasanah Paundu, Ady Wahyudi rezkiawan , runal Rieka Zalzabillah Putri Suparno, I Wayan Syahbudin Syahbudin Wahyudi Sofyan Wardi Wardi Yohannes, Christoforus Yushinta Fujaya Zaenab - Zaenab Muslimin Zagita Marna Putra Zahir Zainuddin Zahir Zainuddin Zahir Zainuddin Zulkifli Tahir