Forecasting of salt demand using ARIMA model to prevent the bullwhip effect in salt supply chain

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Abstract

The volume of imported salt contributed roughly up to 50.29 percent in Indonesia. However, until the end of 2020, salt from domestic farmers reached 2.89 million tons. Based on these conditions, it is necessary to plan how to expand the distribution of local salt. Not only does distribute the salt to the domestic market, but also exports it, so the stock of salt does not accumulate in the warehouse. The work demonstrated in this article constituted to predict the demand of salt especially exported salt. This research utilized the historical demand data from 2014 to 2019 to predict the market of exported salt in Indonesia. The historical data were used to develop several models of autoregressive integrated moving average (ARIMA). This method was used to analysed how the forecast affected to supply chain and to prevent the bullwhip effect on it. The bullwhip effect could be known as the small fluctuations in retail demand level which could cause progressively larger fluctuation in demand at the distributor and supplier levels. The selected model corresponded to the ARIMA (1,0,1) of the tentative models with the smallest RSME value of 9.566. These results will provide to the manager of salt manufacturing to make decisions related to expand the salt market by exporting it rather than only distributing in domestic market.

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APA

Novianti, T., Utami, I. D., & Dania, W. A. P. (2022). Forecasting of salt demand using ARIMA model to prevent the bullwhip effect in salt supply chain. In Journal of Physics: Conference Series (Vol. 2193). Institute of Physics. https://doi.org/10.1088/1742-6596/2193/1/012035

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