Insurance Premium Determination Model Using The Cobb-Douglas Regression Method On Shallot Production

Abstract

The production risk of shallots is very high due to their vulnerability to pest attacks, diseases, and climate change, which creates uncertainty that may cause significant losses for farmers. Insurance protection has therefore become a necessity as an effort to mitigate financial losses and maintain farmers’ stability even in the event of crop failure. Accordingly, this study aims to analyze the production factors of shallots in determining agricultural insurance premiums. The study employs the Cobb-Douglas production function to analyze production factors and the pure premium model to calculate shallot insurance premiums. Data were collected through questionnaires distributed to shallot farmers in Tasikmalaya Regency, with 50 respondents included in the analysis. Based on the results, the determination of shallot insurance premiums using the expectation principle produces higher premium values compared to the standard deviation principle. Premiums under the expectation principle are more sensitive to risk variation, whereas the standard deviation principle tends to yield more conservative and relatively stable premiums. The analysis applies the Cobb-Douglas regression model, with shallot production (Y) as the dependent variable, and land area (X1), seeds (X2), fertilizer (X3), pesticide use (X4), and labor (X5) as independent variables, resulting in a coefficient of determination (R²) of 96.2%. The findings imply that the expectation principle is more appropriate for calculating insurance premiums under conditions of high and fluctuating production risk, while the standard deviation principle is more suitable for relatively stable risk conditions. These results can serve as a basis for formulating agricultural insurance policies that are adaptive to risk variation, while simultaneously promoting more effective financial protection for shallot farmers.