Aplikasi Machine Learning Untuk Forecasting Nilai Overall Equipment Effectiveness Pada Industri Manufaktur

Aufatus Syakira Mardhatillah
Dina Agustina

Journal of Mathematics UNP
Vol 8, No 2 (2023): Journal Of Mathematics UNP

Manufacturing productivity is determined by machine performance. The problem that occurs in production machines is the occurrence of downtime so that the machine does not work optimally. One of the engine performance indicators is OEE. forecasting of the OEE value is needed so that manufactures can take action so they can maintain engine performance. The purpose of this research was to see the results of forecasting OEE value with machine learning linear regression algorithms and see the value of model evaluation with MAPE. The results of the study using training data and testing data obtained a multiple regression model with the variable y is OEE, the intercept coefficient is , and slope coefficient of the availability and performance variables is  and . The model evaluation results are in the range<10%, meaning that the accuracy results had excellent forecasting model.