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CLUSTERING ANDROID MALWARE BERDASARKAN FREKUENSI SYSTEM CALL MENGGUNAKAN K-MEANS

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Penilaian

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In the security sector, malware that specifically attacks smartphones is growing faster and more sophisticated. Malware is becoming more and more powerful in carrying out criminal acts, such as stealing and destroying important data and information stored on mobile phones, thus demanding the creation of an anti-malware system that can prevent and detect when carrying out malware attacks on smart phones. From these results. Based on the research, it shows that the accuracy of the dataset without feature selection is 50% and the dataset with the feature selection method is 60%. Can Lock Feature selection can reduce the number of features that will be used for classification purposes, but does not significantly increase the accuracy of the results.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207004722	T82861	T828612022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T828612022

Publisher

Inderalaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xiv, 52 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.840 7

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Sistem Komputer
Malware

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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