Muhammad Adipa
Universitas Pelita Bangsa

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KLASIFIKASI EMAIL PHISHING MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR Muhammad Adipa; Ahmad Turmudi Zy; M. Makmun Effendi
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 5 No 2 (2023): Agustus
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v5i2.152

Abstract

Saat ini perkembangan teknologi informasi sangat pesat dan cepat, bahkan di Indonesia sendiri. Evolusi teknologi dunia internet terus berlanjut, dan inovasi baru terus bermunculan, membentuk masa depan yang lebih terhubung dan terintegrasi. Namun selain manfaat, muncul tantangan baru, seperti masalah terkait privasi, keamanan siber, dan pengolahan data. Pada satu sisi, perkembangan teknologi informasi yang demikian mengagumkan itu memang telah membawa manfaat yang luar biasa bagi kemajuan peradaban umat manusia. Di sisi lain, berkembangnya teknologi informasi menimbulkan pula sisi rawan yang gelap sampai tahap mencemaskan dengan kekhawatiran pada perkembangan tindak pidana di bidang teknologi informasi yang berhubungan dengan kejahatan mayantara atau “Cybercrime”. Salah satu kejahatan (cybercrime) yang terjadi di Indonesia yaitu Email Phishing. Badan Siber dan Sandi Negara (BSSN) melaporkan, ada 164.131 kasus email phishing di Indonesia pada 2022. Tingginya angka kasus email phishing terus meningkat, oleh karena itu akan dilakukan pengujian untuk mengklasifikasi email phishing menggunakan algoritma K-Nearest Neighbor. Didapatkan hasil akurasi dengan nilai sebesar 84%, precision sebesar 73%, dan recall sebesar 96%. Hasil ini membuktikan bahwa algoritma K-Nearest Neighbor memberikan hasil yang cukup baik dalam mengklasifikasi email phishing. Kata Kunci: Cybercrime, Email Phishing, Klasifikasi, Data Mining, K-Nearest Neighbor Currently the development of information technology is very fast and fast, even in Indonesia itself. The technological evolution of the internet world continues, and new innovations continue to emerge, shaping a more connected and integrated future. But apart from the benefits, new challenges arise, such as issues related to privacy, cyber security, and data processing. On the one hand, the development of such amazing information technology has indeed brought extraordinary benefits to the advancement of human civilization. On the other hand, the development of information technology has also created a dark vulnerable side to the point of worrying about the development of criminal acts in the field of information technology related to mayantara crime or "Cybercrime". One of the crimes (cybercrime) that occurred in Indonesia, namely Email Phishing. The National Cyber ​​and Crypto Agency (BSSN) reported that there were 164,131 phishing email cases in Indonesia in 2022. The high number of phishing email cases continues to increase, therefore a test will be carried out to classify phishing emails using the K-Nearest Neighbor algorithm. Accuracy results were obtained with a value of 84%, precision of 73%, and recall of 96%. These results prove that the K-Nearest Neighbor algorithm gives good results in classifying phishing emails. Keywords: Cybercrime, Phishing Email, Classification, Data Mining, K-Nearest Neighbor