根据生产计划使用线性回归算法预测货物到达的工作流程效率

Bramandito Yusuf Rizqi Affandi, Y. Cahyana, Dwi Sulistya Kusumaningrum, April Lia Hananto, Fitri Marisa
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引用次数: 0

摘要

本研究讨论了一种算法如何产生预测,作为使用线性回归算法实现工作效率的参考。线性回归算法是通过计算因变量和自变量之间的线性关系来进行预测的算法。在他的观察中,研究人员使用了一个样本,即印度尼西亚XYZ PT生产控制部门的货物到达数据,其中In部分为9055551,OUT部分为332037。2022年(2 - 5月)使用线性回归算法进行预测的结果为4981165,使用MAPE(平均绝对百分比误差)方法测试预测结果的结果产生6%的误差,其中6%仍然在A类<10%,这是非常准确的。这一预测的结果产生了人力、空间和航天飞机的效率,减少了1名人力、500平方米的空间和5架航天飞机,每年的总利润为1,897,670,000卢比,并且可以满足新供应商填补仓库面积的需求。研究人员可以得出结论,从以往的研究中,研究人员可以平均90%地找到应用线性回归算法的阶段,过程和结果,可以预测货物的到达并产生工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Work Process Efficiency With Goods Arrival Predictions Against Production Plans Using Linear Regression Algorithms
This study discusses how an algorithm can produce predictions used as a reference for implementing work efficiency using the Linear Regression Algorithm. Linear Regression Algorithm is an algorithm that allows to calculate the linear relationship between the dependent and independent variables to make predictions. In his observations, the researcher used one sample which is data on the arrival of goods in the Production Control department of PT XYZ Indonesia with a total IN part of 9055551, part OUT of 332037. The results of predictions made using the Linear Regression Algorithm in (February-May) in 2022 are 4981165 and on the results of testing the prediction results using the MAPE (Mean Absolute Percentage Error) method produces an error of 6% where 6% is still in category A <10% which is very accurate. The results of this prediction produce Man Power, Space and Shuttle efficiency with a reduction of 1 Man Power, 500m2 space and 5 shuttles with a total profit of Rp. 1,897,670,000 per year and can meet the demand for new suppliers to fill the warehouse area. Researchers can conclude that researchers can find out the stages, processes, and results in applying the Linear Regression Algorithm by an average of 90% from previous studies which can predict the arrival of goods and produce work efficiency.
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