ANALISIS PERBANDINGAN ALGORITMA DECISION TREE DAN NAÏVE BAYES PADA PENDETEKSIAN MALWARE DENGAN DISKRITISASI VARIABEL

Agus Navirgo, Navirgo and Chairani, Chairani (2022) ANALISIS PERBANDINGAN ALGORITMA DECISION TREE DAN NAÏVE BAYES PADA PENDETEKSIAN MALWARE DENGAN DISKRITISASI VARIABEL. Masters thesis, IBI DARMAJAYA.

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Abstract

By the more sophisticated infrastructure, devices and digital technology, people nowadays are living side by side with cyber or the internet. The internet not only has various functions and roles, but also has negative impact; namely cybercrime, one of which is malware. In Indonesia, the threat of cybercrime mostly targets the financial, insurance and property industry sectors, then manufacturing, constructions, and services. Therefore, malware requires special attention. Malware detection techniques are required to determine malware threats, one of which is Classification Algorithm. This study aims to analyze the comparison of the Decision Tree C4.5 Algorithm with the Naïve Bayes on malware detection with variable discretization. The results of the study found that the use of the Decision Tree C4.5 Algorithm is better than the Naïve Bayes. This is proven by the accuracy rate starting from 88.20% to 100%; while the Naïve Bayes starting from 69.60% to 92.10%. These results were obtained by using the Tools Rapidminer Studio with 10-Fold Cross Validation.

Item Type: Thesis (Masters)
Subjects: Ilmu Komputer
eTheses
Divisions: Pasca Sarjana > Magister Teknologi Informasi
Depositing User: AN Agus Navirgo Virgo
Date Deposited: 28 May 2022 01:39
Last Modified: 28 May 2022 01:39
URI: http://repo.darmajaya.ac.id/id/eprint/7341

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