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Predicting the use of the Box - Genghis methods and linear regression of the sales of Diyala Electrical Industries

    Wahhab Jawad Kazem Ahmed Razzaq Abed

Alkut university college journal, 2020, Volume 5, Issue 1, Pages 53-61

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Abstract

Abstract
Abstract A lot of administrative processes or all of them are considered to be one of the most important means, most notably in sales management, which in particular need to be forecasted for sales and for the purpose of sales management so a method or method of forecasting must be used to give precise forecasts. The most prominent of these models are time series models and regression models This study is to find out which methods are better for predicting the volume of sales and which is better. Several criteria have been used to distinguish between the models and the accuracy of the prediction So the best model was determined ARIMA (0, 1, 3) among the several models selected to represent the time series data for being the best as shown in both (MS = 1350488 and AIC = 34.232). The results of the prediction accuracy measurements and the results of the future sales forecast showed that the best and most efficient way to predict is Box Genghis method of linear regression method to predict the sales volume of the General Company for Electrical Industries
Keywords:
    Time Series forecasting box-jenkins linear regression
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(2020). Predicting the use of the Box - Genghis methods and linear regression of the sales of Diyala Electrical Industries. Alkut university college journal, 5(1), 53-61.
Wahhab Jawad Kazem; Ahmed Razzaq Abed. "Predicting the use of the Box - Genghis methods and linear regression of the sales of Diyala Electrical Industries". Alkut university college journal, 5, 1, 2020, 53-61.
(2020). 'Predicting the use of the Box - Genghis methods and linear regression of the sales of Diyala Electrical Industries', Alkut university college journal, 5(1), pp. 53-61.
Predicting the use of the Box - Genghis methods and linear regression of the sales of Diyala Electrical Industries. Alkut university college journal, 2020; 5(1): 53-61.
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