Implementasi Naive Bayes Pada Proxy Server Untuk Klasifikasi Pengguna Internet - Siwi Rahmat Januar; Rakhmadhany Primananda; Muhammad Hannats Hanafi Ichsan (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
The use of internet network access around the world has a very rapid development. A lot of information is taken very easily. the existence of the internet can have adverse impact and have a good impact for its users. With this problem, we need a step to analyze the amount of development criteria internet users by collecting all the information activities requested by users by using a squid server that will be able to Classify the grouping of Internet user character types using naive bayes algorithm. The Naive Bayes Classifier (NBC) can form a probability table as the basis of a classification process that can predict and provide recommendations for processes processed with optimum value. Test results will affect the data classification factors taken in determining the results of the classification. Once found the value of the category naive bayes, then the mikrotik router will be blocking websites containing negative content. From the results of research and testing the determination of clustering can yield the value of Naive Bayes algorithm with accuracy level up to a maximum value of 98.2%.