PERBANDINGAN METODE MOVING AVERAGE, EXPONENSIAL SMOOTING DAN NAIVE METHOD PADA PERAMALAN HASIL PRODUKSI MINYAK GORENG KEMASAN REFILL 400ML, 900ML, DAN 1800ML DI CV. AMALY FOOD

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ABSTRACT

The pattern of data from Cooking Oil Production is very volatile, making it difficult for companies to determine the number of products that will be produced in the future, followed by the difficulty of determining the amount of stock of raw materials provided to meet production needs. Cooking Oil at CV Amaly is made by order only so that future production planning will make it easier for the company in the process of determining strategy and also the supply of raw materials needed. The object of this research focuses on products of the 400ml, 900ml, and 1800ml Gading Sakti pouch types without paying attention to other products. The forecasting method used in this research consists of 3 (three) forecasting methods, namely Single Exponential Smoothing, Moving Average, and Naive method. Forecasting calculations are expected to facilitate the company in the process of determining the strategy and also the inventory of raw materials needed. Forecasting accurate production results is determined by the results of casting calculations with the smallest forecast error value as the final result of the study. The application of the Single Exponential Smoothing Method to forecasting the production of cooking oil for Pounch Gading Sakti 400ml and 1800ml produces data patterns that approach or follow the pattern of production demand data, while the data patterns from the Moving Average Method and the Naïve method tend to be different from the production data. This happens because there is a difference in the calculation of the forecast value between the Naïve method and the Single Exponential Smoothing Method. Meanwhile, for Punch Gading Sakti cooking oil, in 900 ml packaging, the Moving Average method produces a data pattern that is closer to or following the pattern of production demand data than the data pattern of the Moving Average Method and the Nave method. The Exponential Smoothing method has a better accuracy rate than the Moving Average and Nave methods for forecasting Pounch Gading Sakti 400ml and 1800ml. The forecast error value of the Single Exponential Smoothing Pounch Gading Sakti method is 400ml and 1800ml, respectively, 28.59%, 21.89%. The forecast error value of the Moving Average Pounch Gading Sakti method is 400ml and 1800ml, respectively, 29.03% and 24.16%. The forecast error value for the Naïve Pounch Gading Sakti method is 400ml and 1800ml, respectively, 32.74% and 23.90%. Meanwhile, for Pounch Gading Sakti 900 ml, the Moving Average method has a better level of accuracy than the Exponential Smoothing method and the Naïve method. become a reference in the appropriate raw material inventory strategy. As for the production of Punch Gading Sakti cooking oil 900 ml, the results of the Moving Average method forecasting can be a picture of the company in the future as well as a reference in the appropriate raw material inventory strategy.

 

Keywords: Forecast error, Naïve, MAPE, Moving Average, Single Exponential Smoothing


 


Kata Kunci


Forecast error, Naïve, MAPE, Moving Average, Single Exponensial Smoothing

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Referensi


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DOI: http://dx.doi.org/10.55445/teknovasi.v9i2.670

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