Computer Network Management Optimization Through Big Data Analysis Using Time Series Analysis Method

Efficient management of computer networks is becoming increasingly important in the ever-evolving digital age. With the ever-increasing volume of data in the network environment, sophisticated approaches are needed to analyse and optimise network performance. One promising approach is the use of big data analysis with time series analysis methods. In this context, this research aims to explore the potential application of big data analysis using the time series analysis method in computer network management. By combining the power of big data analysis with time series analysis methodology. One of the main applications of big data analysis in computer networks is security threat detection. By analysing unusual traffic patterns or suspicious behaviour, the system can identify potential attacks or data leaks more quickly and efficiently. In addition, big data analytics can also be used to optimise network performance by identifying bottlenecks, predicting capacity requirements, and improving the efficiency of resource usage by utilising big data analytics in the context of computer networks. However, challenges related to data privacy and security remain a major concern that must be addressed in the application of this technology. Therefore, it is important to develop a framework that takes into account the security and privacy aspects of data throughout the big data analysis process. Through this research, it is hoped that innovative solutions to the challenges of managing complex computer networks in the evolving digital era can be found, as well as provide a solid foundation for further research in this field.