Penggunaan Algoritma Decision Tree Untuk Mendeteksi Serangan DDoS Pada Software Defined Network

Kusumayati, Kusumayati (2022) Penggunaan Algoritma Decision Tree Untuk Mendeteksi Serangan DDoS Pada Software Defined Network. S1 Teknik Informatika thesis, STMIK Widya Cipta Dharma.

	Text 1843065-S1-Teknik Informatika.pdf Restricted to Repository staff only Download (1MB) | Request a copy
	Text 1843065-S1-Jurnal.pdf Restricted to Repository staff only Download (1MB) | Request a copy

Abstract

ABSTRAK Kusumayati, 2022, Penggunaan Algoritma Decision Tree Untuk Mendeteksi Serangan DDoS Pada Software Defined Network. Skripsi Jurusan Teknik Informatika, Sekolah Tinggi Manajemen Informatika dan Komputer Widya Cipta Dharma Samarinda. Pembimbing Utama Siti Lailiyah, S.Kom.,M.Kom, Pembimbing Pendamping Pitrasacha Adytia, S.T., M.T. Kata kunci : DDoS (Distributed Denial of Service), Software Defined Network, decision tree, machine learning,python. Keamanan informasi dalam penyimpanan saat ini banyak menggunakan teknologi komputer dan internet,salah satu ancaman yaitu serangan DDoS (Distributed Denial Of Service) yang dilakukan dengan mengirim paket secara terus menerus kepada mesin bahkan jaringan computer juga serangan DDoS terhadap satu entitas di SDN berpotensi berdampak terhadap entitas lain. Untuk mengatasi masalah tersebut, maka mendeteksinya adanya serangan DDoS memiliki beberapa metode dan berbagai macam algoritma, salah satunya algoritma decision tree dan pemilihan metode machine learning dikarenakan proses komputasi yang cepat, akurasi yang tinggi, dan dalam penelitian ini menggunakan metode penelitian SKKNI Nomor 299 Tahun 2020. Tujuan mendeteksi serangan DDoS untuk menghindari kerusakan sistem data atau kehilangan data dari orang jahat agar tidak berdampak kerugian besar, dengan deteksi sejak dini maka upaya penanggulangan serangan DDoS dapat diminimalisir untuk menjaga atau mencegah ancaman system serta memperbaiki system yang rusak. Hasil model pendeteksian yang dibangun melalui proses learning mendapatkan akurasi 99,96 %, precision sebesar 99,88 %, recall 99,86 % , dan fscore sebesar 99.87 %. =========================================================== ABSTRACT Kusumayati, 2022, Use of Decision Tree Algorithm to Detect DDoS Attacks on Software Defined Networks. Thesis of the Department of Informatics Engineering, Widya Cipta Dharma Samarinda College of Informatics and Computer Management. Main Advisor Siti Lailiyah, S.Kom., M.Kom, Assistant Advisor Pitrasacha Adytia, S.T., M.T. Keywords : DDoS (Distributed Denial of Service), Software Defined Network, decision tree, machine learning, python. Information security in storage currently uses computer technology and the internet. one of the threats is DDoS (Distributed Denial Of Service) attacks which are carried out by sending packets continuously to machines and even computer networks as well as DDoS attacks against one entity in SDN which have the potential to have an impact on other entities. To overcome this problem, detecting a DDoS attack has several methods and various algorithms, one of which is the decision tree algorithm and the selection of machine learning methods due to the fast computing process, high accuracy, and in this study using the SKKNI research method No. 299 of 2020 . The purpose of detecting DDoS attacks is to avoid data system damage or data loss from bad people so as not to have a big loss, with early detection, efforts to overcome DDoS attacks can be minimized to maintain or prevent system threats and repair damaged systems. The results of the detection model built through the learning process get 99.96% accuracy, 99.88% precision, 99.86% recall, and 99.87% fscore.

Item Type:	Thesis (S1 Teknik Informatika)
Additional Information:	Pembimbing 1 : Siti Lailliyah, S.Kom.,M.Kom Pembimbing 2 : Pitrasacha Adytia, S.T.,M.T
Uncontrolled Keywords:	DDoS (Distributed Denial of Service), Software Defined Network, decision tree, machine learning,python
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Teknik Informatika
Depositing User:	Ms kusumayati .
Date Deposited:	19 Aug 2022 01:34
Last Modified:	19 Aug 2022 01:34
URI:	http://repository.wicida.ac.id/id/eprint/4414

Actions (login required)

View Item