A Comparative Study of Energy Big Data Analysis for Product Management in a Smart Factory

Energy has been obtained as one of the key inputs for a country's economic growth and social development. Analysis modeling industrial energy are currently time-insertion process because more is consumed in smart factory. This study aims to present analyse predictive models data-driven system be used by appliances find out most significant product item. With repeated cross-validation, three statistical were trained tested test set: 1) General Linear Regression Model (GLM), 2) Support Vector Machine (SVM), 3) boosting Tree (BT). The performance prediction measured R2 error, Root Mean Squared Error (RMSE), Absolute (MAE), Coefficient Variation (CV). best model from (SVM) that able provide 0.86 training data set 0.85 testing with low coefficient variation, this factory Skelp.