Komparasi Performansi Algoritma Naive Bayes dan Logistic Regression pada Malware Android - Andreas Putra Wijaya; Handri Santoso (Universitas Muhammadiyah Purworejo, 2021)
Currently, Indonesian people have used Internet technology for various needs. Starting from transportation, shopping to the world of education using the Internet. Equipment in accessing the Internet varies, ranging from computers, laptops to communication devices such as mobile devices. Currently, mobile devices that are quite widely used by the public are mobile devices based on the Android operating system. In this situation it encourages certain parties to take advantage of loopholes to seek profit, one of which is the creation of Malware. In addition, developments in the field of artificial intelligence are currently very advanced and encourage many researches in various fields to use it. This situation makes researchers focus on malware analysis by utilizing artificial intelligence technology. The purpose of this study is to analyze Android APK files by classifying the Malware family. Performance and accuracy measurements will also be presented in a comparison between the Naïve Bayes algorithm and the Logistic Regression algorithm. The method used is Supervised Learning classification, using Naïve Bayes algorithm and Logistic Regression. Everywhere both methods are Machine Learning algorithms and part of artificial intelligence.