Simple Linear Regression Models for Peanut Production Prediction in North Sumatra 2022

Abstract

Peanuts (Arachis hypogaea L.) are a palm oil commodity that functions strategically in supporting food security and the regional economy. North Sumatra Province has great potential in peanut development, but increasing production is still faced with a number of obstacles. This study aims to examine the relationship between harvest area and peanut production as well as assess the ability of harvest area as a predictor variable of production in North Sumatra Province. This study applies a quantitative approach using a simple linear regression analysis method. The data analyzed is secondary data obtained from the Central Statistics Agency (BPS) of North Sumatra Province through the publication of North Sumatra in Figures 2022, which contains data on harvest area and peanut production at the district/city level. Of the 27 districts/cities, as many as 26 districts/cities were analyzed after going through the data filtering process.

The results of data processing produced a regression equation Y=12.356+0.000592X, which showed that the effect of harvest area on peanut production was positive but very weak. A determination coefficient value (R²) of 3.09% indicates that the harvest area is only able to explain a small part of the variation in production, while most of it is influenced by other factors outside the model. Significance testing through the F-test and t-test showed that the regression model was not significant at a 95% confidence level. These findings confirm that increasing peanut production cannot rely solely on land expansion, but rather requires an intensification strategy through increased productivity and input efficiency.