ESTIMATION OF COPRA INDUSTRY REVENUE USING MULTIPLE REGRESSION ANALYSIS

This study utilized Multiple Regression Analysis to construct a predictive model for estimating copra industry revenuein Davao Oriental. Key predictors included selling price, production, and production cost. The secondary data fromthe Philippine Coconut Authority, Davao Oriental, regarding the 2022 crop cycle of copra farmers across elevenmunicipalities, was analyzed. The researchers employed a stratified proportionate random sampling method to select383 samples. The multiple linear regression analysis produced a model with positive coefficients for all revenuepredictors, indicating that increased selling price, production, and production cost positively impacted copra revenuewhile other variables were constant. The model demonstrated reliability with a strong coefficient of determination anda p-value below 0.05, denoting its significance in revenue prediction. Model validity was confirmed through splitsample analysis, consistently showing a strong coefficient of determination, significant predictive power, and positivecoefficients for all variables. These outcomes emphasized the credibility and reliability of the regression in forecastingcopra industry revenue in Davao Oriental, providing valuable insights for policymakers, industry stakeholders, andresearchers to formulate informed decisions and targeted strategies.