Predicting Network Bandwidth Usage: Case Study at PT. Bank ABC

The development of the internet network is now comprehensive and an essential requirement for digital competition companies. All activities that used to be done manually are slowly transforming into digitization and automation. In this process, an internet network is needed, so it is necessary to fulfill internet networks' availability. In this paper, an analysis is conducted to optimize network bandwidth requirements at PT. Bank ABC uses data mining techniques. The data mining method is carried out using predictive techniques using three algorithms, namely Deep Learning, Generalized Linear Model and K-Nearest Neighbors, each of which is tested using split data models and cross-validation. Of these three algorithms, the Generalized Linear Model algorithm produces the highest accuracy value.