Prediksi Harga Gabah Kering Panen Menggunakan Exponential Smoothing dan Weighted Moving Average

Abstract

Rice is one of the staple food ingredients for Indonesian people. In this study the authors predict the price of dry harvested unhulled rice which can help in estimating the price of dry harvested unhulled rice in the next period. In this study, the authors obtained price data for dry harvested unhulled rice from the Central Bureau of Statistics for West Java Province. In processing the price of dry harvested unhulled rice, the author uses the python programming language with Jupyter Notebook, uses the Weighted Moving Average and Exponential Smoothing methods to find out which method is the best of the two in predicting the price of dry harvested unhulled rice. From the results of this study, it was found that the best method for predicting the price of dry harvested unhulled rice was the Exponential Smoothing method α=0.9 with the smallest RMSE compared to using the Weighted Moving Average and Exponential Smoothing methods α=0.1 α=0.2 α=0.3 α=0.4 α=0.5 α=0.6 α=0.7 α=0.8. The author makes a design program for predicting the price of dry harvested unhulled rice according to the Exponential Smoothing method α=0.9 using the Python programming language with streamlit so that can find out the price prediction for dry harvested unhulled rice easily, quickly and precisely.