RISK MODELING OF BLAST DISEASE (PYRICULARIA ORYZAE) IN RICE CROPS USING A REGRESSION APPROACH AND THE COBB-DOUGLAS MODEL

Blast disease, caused by the fungus Pyricularia oryzae, is one of the major diseases affecting rice plants and can result in significant yield losses. Environmental factors, particularly climatic conditions, play a role in influencing the development of disease outbreaks. This study aims to develop a risk model for blast disease outbreaks in rice plants using a multiple linear regression approach and the Cobb-Douglas function model. The study was conducted in three rice-producing centers in North Sumatra Province—Deli Serdang, Langkat, and Serdang Bedagai Regencies—using data from five growing seasons between 2023 and 2026. The variables analyzed included temperature, humidity, rainfall, and the extent of rice blast disease outbreaks. The analysis was performed using the Ordinary Least Squares (OLS) method with the aid of statistical software. The results of the study indicate that climatic factors have varying effects across regions. Rainfall was the climatic factor that had the most dominant effect on blast disease outbreaks in Langkat Regency, with a significance value of 0.002 and a standardized coefficient of 0.641. Meanwhile, temperature and humidity did not show a significant effect in several observation areas. The resulting risk model can be used as a basis for developing a blast disease outbreak prediction system and to support more effective decision-making regarding disease control.