Forecasting Needs Of Mountain Types Of DDD Bike Using The Seasonal Autoregressive Integrated Moving Average Model Approach Peramalan Kebutuhan Sepeda DDD Jenis Gunung Dengan Pendekatan Model Seasonal Autoregressive Integrated Moving Average
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Published:
Jul 16, 2021
Keywords:
forecasting, SARIMA, Box Jenkins
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Abstract
One of the bicycle manufacturers in Indonesia, namely PT. DDD is a manufacture engaged in the production of various types of bicycles with a make to stock production system. Market demand that fluctuates every year results in a lack of readiness to meet market needs. So a re-planning is needed in order to meet all market demands. The Box Jenkins statistical method, the Seasonal Autoregressive Integrated Moving Average model, is one of the appropriate approaches to solve problems at PT. DDD. The advantages of the SARIMA model can be used to forecast seasonal or non-seasonal time series simultaneously. The best SARIMA model approach to forecasting demand for mountain bikes at PT. DDD is SARIMA (0,0,0)(0,1,1)12 with the equation Zt=Zt-12+ΘQat-12+at with the smallest MAPE value of 32.35%. So that the model is said to be feasible to predict mountain bikes and the model can predict up to 12 periods in 2021.
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How to Cite
[1]
D. Muhjidin and T. Sukmono, “Forecasting Needs Of Mountain Types Of DDD Bike Using The Seasonal Autoregressive Integrated Moving Average Model Approach ”, PELS, vol. 1, no. 2, Jul. 2021.
Section
Industrial Engineering
References
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