REGRESSION MODEL ON PAGARALAM COFFEE FARMERS’ INCOME WITH THE INFLUENCE OF THE USE OF HERBICIDE REDUCTANT VARIABLE

Abstract

The existence of weeds in coffee fields will become competitors for coffee plants, so that they can be economically and ecologically detrimental. Inappropriate use of chemical herbicides can have a negative impact. Herbicide reductants made from organic are used in weed control. This study aims to analyze the variables that affect the net income of Pagaralam coffee farmers using multiple linear regression analysis. One of these variables is a qualitative variable in the form of categories of respondents based on the use of herbicide reductants. The data used was obtained from the results of questionnaires on 56 respondents who are users and 80 respondents who are not users of herbicide reductants. The results of the hypothesis test of mean difference found that the net income of the two respondent categories is not different. The regression analysis also resulted that there was no significant difference in net income between the two respondent categories. Variables that had a significant effect on net income included gross income, farming maintenance costs, estimated yields, and tree age. Several models also contain variables of land area, length of time in coffee farming, number of trees, and frequency of organic fertilizers used. Old coffee trees should be treated better with the use of organic fertilizers and also wise weed control techniques.