Ngudiantoro, Ngudiantoro and Irmeilyana, Irmeilyana and SAMSURI, MUKHLIZAR NIRWAN (2020) Binary Logistic Regression Modeling on Net Income of Pagar Alam Coffee Farmers. International Journal of Applied Sciences and Smart Technologies, 2 (2). pp. 47-66. ISSN p-ISSN 2655-8564, e-ISSN 2685-9432
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Abstract
Pagar Alam Coffee is a Besemah coffee originating from the Smallholder Plantation in South Sumatra, Indonesia. The majority of Pagar Alam coffee farming is a hereditary business. Coffee farmers' income is very dependent on coffee production, production costs, and coffee prices. This study aims to obtain a probability model of Pagar Alam coffee farmers income based on the factors that influence it. The independent variables studied were the number of dependents, economic conditions, number of trees, age of trees, frequency of fertilizer used, frequency of pesticide used, production at harvest time, production outside harvest time, number of women workers outside the family, minimum price of coffee, maximum price of coffee, farmers' gross income, and land productivity. Modeling used binary logistic regression method on 179 respondents. There were three methods used, i.e. enter method, forward and backward methods. The model using enter method results the greatest prediction accuracy which is 87.7%. The factors that have a significant influence on the net income of Pagar Alam coffee farmers are gross income, land productivity, and the number of women workers from outside the family. The most influential variable is gross income. Keywords: Net income, gross income, Pagar Alam coffee farmers, binary logistic regression
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA1-43 General |
| Divisions: | 08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1) |
| Depositing User: | Mrs Irmeiliana Irmeiliana |
| Date Deposited: | 13 Dec 2020 16:14 |
| Last Modified: | 13 Dec 2020 16:14 |
| URI: | http://repository.unsri.ac.id/id/eprint/38437 |
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