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首页> 外文期刊>Procedia Computer Science >Performance Comparisons between Arima and Arimax Method in Moslem Kids Clothes Demand Forecasting: Case Study
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Performance Comparisons between Arima and Arimax Method in Moslem Kids Clothes Demand Forecasting: Case Study

机译：穆斯林儿童服装需求预测中Arima和Arimax方法的性能比较：案例研究

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摘要

The Moslem kids clothes demand in Habibah Busana are likely increase at certain times, especially near the Eid-holidays. that total demands in each year is varies and always increase when near the Eid holidays. The demand always increases when near Eid-holidays but decrease in next month. It's repeat every year but unfortunately it occur in different time every year. it means that Eid holidays occur in different time every year. It make the company in uncertainty condition. This research compare Arima method which make forecast in univariate data and Arimax as multivariate method which include independent variables such as different time of Eid holidays every year. The result show that Arimax method is better than Arima method in accuracy level of training, testing, and next time forecasting processes. There are minimum fourteen variables have to include in Arimax model in order to make accuracy level is not decrease.
机译：Habibah Busana的穆斯林儿童服装需求在某些时候可能会增加，尤其是在开斋节假期附近。每年的总需求是变化的，并且在开斋节假期前后总是增加。临近开斋节假期，需求总是增加，但在下个月减少。每年重复一次，但不幸的是，它每年在不同的时间发生。这意味着开斋节假期每年在不同的时间发生。这使公司处于不确定状态。本研究比较了在单变量数据中进行预测的Arima方法与在包括每年不同的Eid假期时间等自变量的Arimax变量中进行的比较。结果表明，在训练，测试和下次预测过程的准确性水平上，Arimax方法优于Arima方法。为了使精度等级不降低，Arimax模型中必须包含最少14个变量。

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