Naive Bayes untuk Klasifikasi Pergantian Operating System pada Personal Computer di Bank X - Syifa Namira Neztigaty; Dian Eka Ratnawati; Dany Primanita Kartikasari (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
Bank X is one of the largest banks in Indonesia. The Desktop Team, which is one of the teams that carry out risk identification and periodic evaluation on PCs. Through this evaluation, the Desktop Team found many operating systems on PCs at Bank X were end-of-support. This condition poses a risk if there are bugs or security holes in the operating system that can lead to data theft. In order to avoid this incident, the entire operating system of end-of-support PCs must be replaced with a newer operating system. Currently the operating system replacement activity has been carried out, but it is still done manually and has not been effective. The process has succeeded in replacing Â±5,000 PCs. Through this system, the Desktop Team Desktop Team will get the class results from the PC. The data could be classified by using data mining classification method, namely Naive Bayes. From the PC attribute data does not yet have a class, the system will perform data processing. Then the data is calculated using the existing functions on the controller, by accessing classified PC database. Information about the classification results is displayed on the prediction results page. From the results of testing the accuracy value is 92.8371%.