Analysis of Food Needs and Availability of the MBG Program in Poso Regency Using a Linear Regression Model

Abstract

Food availability is a key factor in maintaining the sustainability of the Free Nutritional Food Program (MBG), especially in areas dependent on local supplies such as Poso Regency. Accurate food needs planning is crucial for optimal and sustainable distribution and fulfillment of community nutrition needs. This study aims to analyze the relationship between various types of food and total food needs and to determine variables that significantly influence the MBG program using the Multiple Linear Regression method. This study uses a quantitative approach with descriptive statistical analysis and classical assumption testing, including normality, multicollinearity, autocorrelation, and heteroscedasticity tests. Eight independent variables such as rice, eggs, cooking oil, and shallots were analyzed against the dependent variable of total food needs using Excel and SPSS software. The results showed that Rice (X₁) and Shallots (X₈) were variables that significantly influenced total food needs. The linear regression model produced an R² value of 0.5394, indicating that 53.94% of the variation in food needs can be explained by the variables in the model. The multiple linear regression model proved quite accurate in explaining the relationships between variables. These findings underscore the importance of data-driven planning in managing the MBG program, particularly in ensuring the sustainable availability of staple foods in Poso Regency.