PERAMALAN HARGA PASAR TELUR AYAM RAS MENGGUNAKAN VECTOR AUTOREGRESSIVE (VAR) (Studi Kasus: Harga Pasar Telur Ayam Ras di eks Karesidenan Surakarta Tahun 2020-2022)

Abstract

The stabilization of the market price of broiler eggs is one of the points that the government should pay attention to. This is to prevent significant price increases or decreases. Government precautions to keep broiler egg prices stable can be done through forecasting. Vector autoregression (VAR) is a time series model that can be used to model and forecast data containing multiple variables at once. VAR models were constructed to estimate relationships between economic variables without paying attention to exogenous issues. The level of predictive accuracy of vector autoregressive (VAR) models can be seen from the SMAPE value. The smaller the SMAPE value, the better the prediction results. The data used are the weekly prices of broiler eggs in Kab. Boyolali, Kab. Karanganyar, Kab. Klaten and Surakarta from January 2020 to June 2022. The vector autoregression (VAR) method prediction gave his SMAPE values of 13.48% for Kab. Boyolali, 13,38% Kab. Karanganyar, 13,86% of the price of broiler eggs in Kab. Klaten and 13.25% of the variable price of broiler chicken eggs in Surakarta city. The SMAPE values are between 10% and 20%, so the prediction accuracy is good.