Analysis of the Influence of CPU Specifications on System Performance Using Linear Regression

The development of computer technology demands an increase in optimal system performance, especially in the Central Processing Unit (CPU) component as a data processing center. CPU performance is affected by various hardware specifications such as machine cycle speed, primary memory capacity, cache, and number of input/output channels. This study aims to analyze the influence of CPU specifications on system performance using linear regression methods. The data used is secondary data on CPU specifications and performance processed using the RapidMiner application. The research methods include the data collection stage, data preprocessing, linear regression modeling, and model evaluation using the Root Mean Square Error (RMSE) value and determination coefficient (R-squared). The results show that several CPU specification variables have a significant influence on system performance. The resulting linear regression model is able to predict CPU performance with a good level of accuracy so that it can be used as a tool in analysis and decision-making related to computer hardware selection.