APLIKASI REGRESI BERGANDA PADA FAKTOR-FAKTOR YANG BERPERAN DALAM MENENTUKAN PENDAPATAN PETANI MANGGA

Abstract

One of the leading agricultural commodities in Indonesia is mango fruit. Apart from being rich in health benefits, this commodity also has high economic value. West Java Province is one of the provinces with the highest mango production in Indonesia. This can happen because West Java has mango production center areas, one of these areas is Majalengka Regency. Even though the mango commodity in this Regency has relatively high economic potential, in the field the income of business actors often fluctuates. Based on this explanation, this research aims to analyze the factors that influence mango farming income in Majalengka Regency using the multiple linear regression method. Data was collected through a survey of 130 mango farmers using a questionnaire. The results of the analysis show that the total land area has a significant negative effect on income, while the total number of mango trees and average capital per year have a significant positive effect. Other factors such as training frequency, highest yield from one tree, and farmer age also have a positive influence on income, although not significant. The F test shows that the regression model is significant and can be used to predict mango farming income with an R Square value of 0.852716.

Key-words: income, mango farming business, multiple linear regression, majalengka regency, income factors.