Modeling Rice Production in West Java by Means Geographically Weighted Regression

Abstract

In Indonesia, rice production varies from province to province, resulting in both large and small disparities between provinces. In Indonesia, East Java, Central Java and West Java Provinces have the highest rice production. In contrast to East Java and Central Java, however, the total rice consumption per year in West Java is the highest. In linear regression, the coefficients are the same for all regions, while each region sometimes has different influencing factors, resulting in spatial diversity. Consequently, the Geographically Weighted Regression (GWR) method was used to model the rice production of West Java Provincial regencies/municipalities by accounting for spatial heterogeneity. The GWR model employs the fixed bi-square kernel function as its weighting function. This model includes five explanatory variables, such as number of agricultural labor, number of used rice seed, number of two-wheel tractor, number of water pump, and number of farmer groups, with rice production as the response variable. GWR model has greater coefficient determination (96.8 percent) and smaller AIC values (920.76) than global regression. During the period of 2018-2020, the number of two-wheel tractors and the number of water pumps had the greatest impact on rice production in West Java and the number of two-wheeled tractors and the number of farmer groups variables has an effect on rice production in most regencies/municipalities in West Java. There are 11 groups of areas which has the similarity of significant predictor variables.