HIGH AVAILABILITY IN SERVER CLUSTERS BY USING BACKPROPAGATION NEURAL NETWORK METHOD

Ahmad Heryanto; Aditya Gunanta

doi:10.36378/jtos.v4i1.936

Ahmad Heryanto
Aditya Gunanta

DOI: https://doi.org/10.36378/jtos.v4i1.936

Keywords: Client, Server,, Kluster,, High Availability,, Neural network

Abstract

Server is a host device applications to serve every request in finding information needs. The server must fully support the services used for the organization's digital needs 24 hours in a day, 7 days in a week, and 365 days in a year. The concept of High Availability is needed to maintain the quality of server services. The algorithm used to build HA can use both classical and modern algorithms. The algorithm used in this research is using backpropagation neural network. In this study, the parameter values to obtain optimal accuracy are learning rate 0.1, training data 80 and test data 20, the number of nodes in hidden layer 4, minimum error 0.0001, and the number of iterations 2500.The best accuracy value using these parameters is 93.79% .

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