KLASIFIKASI ANDROID MALWARE MENGGUNAKAN ALGORITMA PRINCIPAL COMPONENT ANALYSIS (PCA) DAN RANDOM FOREST

SORAYA, DYAH CITRA and Stiawan, Deris (2020) KLASIFIKASI ANDROID MALWARE MENGGUNAKAN ALGORITMA PRINCIPAL COMPONENT ANALYSIS (PCA) DAN RANDOM FOREST. Undergraduate thesis, Sriwijaya University.

	Text RAMA_56201_090112815107.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_56201_090112815107-TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (8MB) | Request a copy
Preview	Text RAMA_56201_090112815107_0003047905_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (1MB) | Preview
	Text RAMA_56201_090112815107_0003047905_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (404kB) | Request a copy
	Text RAMA_56201_090112815107_0003047905_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (802kB) | Request a copy
	Text RAMA_56201_090112815107_0003047905_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_56201_090112815107_0003047905_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (99kB) | Request a copy
	Text RAMA_56201_090112815107_0003047905_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (181kB) | Request a copy

Abstract

More and more parties are harmed because currently malware can infect almost all operating systems. One type of Android malware is MazarBot. Mazarbot is very dangerous because when it is installed on a device it can access, spy on and control the device secretly remotely. That way the attacker can manipulate and do whatever he wants because he gets full access to the victim's device. The Random Forest method can be applied in classifying Android Malware. Where the Android Malware classification focuses on Mazarbot and Benign malware using a dataset called CICAndMal2017. In addition, the Principal Component Analysis (PCA) method is also applied in this study, its function is to reduce the number of high data dimensions to lower data dimensions. The accuracy results obtained by applying the Random Forest method is 92.06%. Meanwhile, the accuracy of using a combination of the Random Forest method with PCA is 82%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Android, malware, klasifikasi, Random Forest, Principal Component Analysis (PCA)
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. T Technology > T Technology (General) > T10.5-11.9 Communication of technical information T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control) T Technology > T Technology (General) > T58.6-58.62 Management information systems
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 9639 not found.
Date Deposited:	11 Jan 2021 02:50
Last Modified:	11 Jan 2021 02:50
URI:	http://repository.unsri.ac.id/id/eprint/39483

Actions (login required)

View Item