Taxation of Palm Oil Production Results Using on Regression Model (PT. Menthobi Makmur Sustainable)

Wandha Atmaja Aji, B. Nugroho, Toyyibah Toyyibah
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引用次数: 2

Abstract

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.
基于回归模型的棕榈油生产税收结果分析(PT. Menthobi Makmur Sustainable)
PT Menthobi Makmur Lestari是棕榈油生产领域的一家成长中的工业公司。该公司的目标是增加棕榈油产量,以预测产能计划和制造设施。使用的预测方法之一是多元线性回归。用于预测的自由变量是树的年龄、土地面积(ha)、树的数量、葡萄藤的数量,约束变量是油棕的产量。多元回归相关检验结果显示,相关系数小于等于0.05。假设检验包括多元线性回归和相关分析,采用t检验和f检验,显著性水平为α = 0.05。多重相关分析(R)值为0.947,决定系数为90%。多元回归方程的性能是预测的准确性,平均绝对错误率(MAPE)为21%,这是由训练和测试数据的验证形成的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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