KLASIFIKASI ADWARE MALWARE PADA ANDROID DENGAN METODE RANDOM FOREST

HARDIANTO, NOVIT and Stiawan, Deris and Heryanto, Ahmad (2020) KLASIFIKASI ADWARE MALWARE PADA ANDROID DENGAN METODE RANDOM FOREST. Undergraduate thesis, Sriwijaya University.

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Abstract

The development of technology triggers the development of malicious files called malware. Malware is software that is explicitly designed with the aim of finding weaknesses or even damaging software or operating systems. In this study, the dowgin and benign malware classification was carried out using the Random Forest algorithm method by comparing weka data and spyder programs. The dataset used in this study is the CICAndMal2017 csv (Comma Separated Values) category with the dowgin type in this dataset has 1197 for 53% dowgin data and 792 begign data or 47% where this dataset has 85 attributes. After the classification, the accuracy value for the accuracy value is 0.998% and the OOB Error value is 0.16%, while using the Random Forest method the accuracy value for the spyder program is 0.891% and the OOB Error value is 0.108%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Adware Malware , Weka , Spyder, Random Forest
Subjects:	T Technology > T Technology (General) > T10.5-11.9 Communication of technical information T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T10.7 Technical literature T Technology > T Technology (General) > T1-995 Technology (General) > T11 General works > T11.9 Technical archives Industrial directories Industrial directories T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T11 General works > T11.9 Technical archives Industrial directories Industrial directories T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T11.9 Technical archives Industrial directories Industrial directories
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 9646 not found.
Date Deposited:	11 Jan 2021 03:21
Last Modified:	11 Jan 2021 03:21
URI:	http://repository.unsri.ac.id/id/eprint/39522

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