Implementation Vector Autoregressive (Var) On Rice Production and Rice Productivity Data in Indonesia

Abstract

Vector Autoregressive (VAR) is a statistical model used to analyze multivariate time series, especially in time series where the variables have a relationship that influences each other over time. This study aims to determine the relationship between rice production and rice productivity in Indonesian. The data used in this study is secondary rice commodity data based on rice production and rice productivity in Indonesian from January 2014 to December 2018. The Augmented Dickey-Fuller method in this study was used to carry out a stationary test on the data. The ACF and PACF graphs show that rice commodity data based on rice production and rice productivity can be modeled using VAR. Based on the VAR(1) model, that rice production and rice productivity influence each other. The R2 and Adjusted R2 values for each partial equation of the VAR model (1) tend to be small so that the diversity of the models for each equation cannot be explained by the variables of rice production and rice productivity in Indonesian.