ANALISIS PERBANDINGAN ALGORITMA HIDDEN MARKOV MODEL DAN ALGORITMA NAIVE BAYES DALAM MEMPREDIKSI SERANGAN PADA WEB SERVER - Hilmy Baskoro (2022)
The website is an application that is easily accessible anywhere and anytime, in that convenience there is an attack that can be carried out on a website that is aimed directly at the web server. A user who accesses a server will be recorded by the system and will be recorded as a datalog, as well as if an attacker who wants to do hacking by penetrating a security hole in a website will be recorded as a log because he has accessed the website. The datalog will be a dataset that can be processed in this research for classification of attacks and not attacks on a web server. But not all data mining algorithms have good performance in classifying types of attacks. Therefore, this study tries to compare the two classification algorithms contained in data mining and use the SIAKAD UPNVJ website server log dataset that has been obtained. The data will be trained and tested for attack and non-attack classification and compared using two data mining classification algorithms, namely the Hidden Markov Model algorithm and the Naïve Bayes algorithm so as to get a result in the form of accuracy, precision and recall which is the best between the two algorithms.