FATMAWATI, ALFIAH NUR and Stiawan, Deris and Afifah, Nurul (2024) PENERAPAN RANDOM FOREST CLASSIFIER UNTUK DETEKSI PDF MALWARE PADA LAYANAN AGREGATOR GARBA RUJUKAN DIGITAL (GARUDA) KEMENDIKBUD DIKTI. Undergraduate thesis, Sriwijaya University.
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Abstract
Garba Rujukan Digital (GARUDA) is a Service Provider whice provides information and means which has been produced by research academics in Indonesia, Currently the service (GARUDA) Provides data in file room. Portable Document Fortmat (PDF). Whice PDF is ussually for fast and easy information sharing service, Howaver many people are irresponsible and actually tak and advantage of this to commit digital crime Cyber Crime. (GARUDA) hava data a big and give a 10000 PDF Malware is used for dataset in research. Dataset in mine then get it data benign 8900, data non-pdf 196, and data mal-pdf 6. Virus Total and PDFiD in used for analysis statis to dataset, This research arms to produce performance and evaluation of the performance of the Random Forest algorithm in the Imbalance dataset on the GARUDA malware PDF dataset. The data balancing process is carried out using two approaches, namely using Over-sampling with the SMOTE technique and Under-sampling as well as using K-Fold. The application of the Random Forest Classifier resulted in an accuracy rate of 86.22%, precision with 79.55%, recall with 78.98% and F1-Score with 79.26%.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Random Forest Classifier, PDF Malware, Virus Total, PDFiD, Synthetic Minority Over-sampling Technique SMOTE |
Subjects: | T Technology > T Technology (General) > T1-995 Technology (General) |
Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
Depositing User: | Alfiah Nur Fatmawati |
Date Deposited: | 26 Jan 2024 06:26 |
Last Modified: | 26 Jan 2024 06:26 |
URI: | http://repository.unsri.ac.id/id/eprint/139960 |
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