Food security is a condition where food is fulfilled for a household which is reflected in the availability of sufficient food both in terms of quantity and quality, safe, and equitable and affordable. In Government Regulation No. 38 of 2007 Food security has become a basic prerequisite that must be owned by autonomous regions where food security is a mandatory matter for the central, provincial, and district / city governments. To measure the food security of a region, the Government makes an indicator in looking at the achievement of food security of a region. This indicator is the Food Security Index. For this reason, it is necessary to conduct an analysis to model factors related to food security through the Food Security Index to see how much these factors contribute to the ups and downs of the Food Security Index. One statistical method that can explain the relationship between predictor variables and response variables is spline nonparametric regression analysis. Spline is an approach towards matching data while taking into account the smoothness of curves. Splines have the advantage of overcoming data patterns that show sharp rises / downs with the help of knot points, and the resulting curve is relatively smooth. The research objective of this study was to determine the modeling of the Food Security Index in North Sumatra using the Multivariable Spline Regression Method. Based on the analysis that has been done, a spline regression model for the Food Security Index in North Sumatra was obtained at three knot points with a minimum GCV value of 27.39 and R^2 is 92.76%.
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