Analysis And Forecasting of Foodstuffs Prices in Bandung Using Gated Recurrent Unit

Abstract

Bandung is a city in West Java province, Indonesia. Bandung becomes one of the most densely populated cities in Indonesia. Therefore, predicting and analyzing the prices of foodstuffs based on historical data is necessary to provide useful information for society and government. This paper developed models implementing a gated recurrent unit or GRU which is a specific version of recurrent neural networks (RNN) for forecasting the price of rice, chicken meat, chicken egg, shallot, and garlic in a Bandung traditional market. The GRU models are trained using a dataset from the Information Center for National Strategic Food Price. The data are recorded from January 2018 – February 2023. The experimental results show that GRU was successfully implemented for forecasting the price of rice, chicken meat, chicken egg, shallot, and garlic. The best models produce Mean Absolute Error (MAE) as 4.3, 133.1, 118.3, 341.8, and 338.1 for rice, chicken meat, chicken egg, shallot, and garlic, respectively.