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Shallot Price Forecasting in Three Locations in Indonesia Using Generalized Space-Time Autoregressive Model Lidwina Galuh Wandira; Mike Prastuti
IPTEK The Journal of Engineering Vol 10, No 1 (2024)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v10i1.a17592

Abstract

Shallots are one of the commodities that have an important role for the economy in Indonesia. Many shallot farmers, especially in production center areas, depend for their economy on shallot farming. The price of shallots in Indonesia during 2010-2022 fluctuated quite a bit. This is because the demand for shallots tends to increase over time, while shallot production is seasonal, and the distribution is uneven. The fluctuation of shallot prices and the huge costs of shallot farming result in risk and uncertainty for farmers. The forecasting method used is Generalized Space-Time Autoregressive (GSTAR). The results of the best model for predicting shallot prices in three locations in Indonesia, namely Cirebon, Tegal, and Madiun based on RMSE values, namely the GSTAR (31)-I(1) model use inverse distance normalization weights. Forecasting results for the highest shallot prices in Cirebon, Tegal and Madiun occur in the first week of August 2022. Meanwhile the lowest shallot prices in Cirebon and Madiun occur in the fifth week of August 2022, however the lowest shallot prices in Tegal occur in the fourth week of August 2022. Shallot price movement patterns in Cirebon, Tegal, and Madiun for the next 14 periods will continue to fluctuate but tends to show a downward trend. This was caused by several regions entering the harvest season, resulting in a spike in yields at the same time. As a result, the yield of shallots in the three locations was abundant and caused the price of shallots to decrease.