International Journal of Academic and Applied Research (IJAAR)   Year: 2023 | Volume: 7 | Issue: 6 | Page No.: 67-71 Modeling of Provincial Food Security Index in Indonesia based on Probit Ordinal Panel Regression Approach with Random Effects Download PDF Anisa Laila Azhar, Suliyanto, Nur Chamidah, Dita Amelia, Elly Ana Abstract: Indonesia has been renowned as an agricultural nation, giving paramount importance to agriculture in meeting its food requirements. Due to its large population, there is a significant demand for food, and insufficient food supply can jeopardize the country's food security. This research aims to develop a model for the food security index and determine the factors influencing provincial food security in Indonesia using the probit ordinal regression method with panel data and random effects. The analysis reveals that variables such as the percentage of households with access to electricity, the percentage of stunted toddlers, and rice production have a substantial impact on the provincial food security index in Indonesia. Moreover, the panel probit regression model with random effects achieves a classification accuracy of 44.83% and an AIC value of 236.79, surpassing the standard ordinal probit regression model. This conclusion is further supported by the model suitability test, which yields a p-value of 0.000, indicating that the panel ordinal probit regression model with random effects is more suitable than the standard probit regression model.