PT Menthobi Makmur Lestari is a growing industrial company in the field of palm oil production. The company is targeting increased palm oil production to forecast capacity plans and manufacturing facilities. One of the prediction methods used is multiple linear regression. The free variables used for prediction are the age of the tree, land area (ha), number of trees, number of vines, and the bound variable is the yield of oil palm production. The results of the correlation test using multiple regression showed a significant correlation of 0.05 or less. Hypothesis testing includes multiple linear regression and correlation using the t test and f test with a significance level of α = 0.05. The value of multiple correlation analysis (R) is 0.947 and the coefficient of determination is 90%. The performance of the multiple regression equation is the accuracy of predictions with an average absolute error percentage (MAPE) of 21%, which is formed from the validation of training and testing data.

Work effectiveness is greatly influenced by organizational development, placement, and use of work. Productivity at work has a big impact on results. This study aims to identify the impact of determinants of labor productivity as an oil palm harvester in oil palm plantations in order to increase knowledge, skills and experience in work. Data on the labor productivity of oil palm harvest was carried out by Purpose sampling of 76 people taken from 6 stagnation in 3 afdeling related to wages and premiums obtained every month. Data analysis using descriptive methods and multiple linear regression. Multiple regression analysis partially shows that education level, number of dependents, and age have no real effect on labor productivity, but length of work does. Simultaneous regression tests show that education level, number of dependents, age, and length of working hours have a significant effect on the labor productivity of oil palm harvests.