KLASIFIKASI MALWARE RANSOMWARE BERBASIS TEKNIK SELEKSI FITUR DENGAN ALGORITMA K-NEAREST NEIGHBOR

PERDANA, TATA SATRIA TIMOR and Heryanto, Ahmad (2021) KLASIFIKASI MALWARE RANSOMWARE BERBASIS TEKNIK SELEKSI FITUR DENGAN ALGORITMA K-NEAREST NEIGHBOR. Undergraduate thesis, Sriwijaya University.

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Abstract

Malware adalah sebuah perangkat lunak yang dibuat dengan tujuan memasuki dan terkadang merusak sistem komputer, jaringan, ataupun server tanpa diketahui oleh pemiliknya, Ransomware merupakan jenis malware tertentu yang akan menuntut tebusan finansial dari korban dengan cara mengancam akan mempublikasikan, menghapus, atau juga menahan akses ke data pribadi yang penting. Pada penelitian ini akan melakukan klasifikasi terhadap malware ransomware berjenis lockerpin dengan berbasis teknik seleksi fitur dan menggunakan algoritma K-Nearest Neighbor. Teknik Correlation dan Univariate yang akan digunakan untuk tahap seleksi fitur yang kemudian akan di ambil fitur-fitur yang terbaik dan relevan. Dari hasil tersebut akan di lanjutkan dengan proses klasifikasi dengan menggunakan algoritma K-Nearest Neighbor, dengan melakukan 3 percobaan. Hasil yang didapatkan pada percobaan pertama Correlation 97,83% untuk Univariate 97,87%, percobaan kedua correlation 98,37% untuk univariate 98,80% dan percobaan ketiga correlation 98,80% untuk univariate 98,82%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Malware, Ransomware, Lockerpin, K-Nearest Neighbor, Correlation, Univariate.
Subjects: T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television > TK5105.585.S724 Computer networks Internet (Computer network) Computer networks--Standards Quality control
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Users 5623 not found.
Date Deposited: 19 Oct 2021 01:48
Last Modified: 19 Oct 2021 01:48
URI: http://repository.unsri.ac.id/id/eprint/56068

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