Analisis Pengaruh Luas Lahan, Tenaga Kerja, dan Harga terhadap Pendapatan Petani Sawit (Studi pada Kecamatan Muara Tabir Desa Pintas Tuo) Analysis of the Effect of Land Area, Labor, and Price on Oil Palm Farmers' Income (A Study in Muara Tabir Subdistrict, Pintas Tuo Village)
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Page Numbers:
749-766
Digital Object Identifier:
10.58578/arzusin.v6i1.9161
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Authors:
Tri Evita Safutri1, Usdeldi Usdeldi2, Syahril Ahmad3 
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Abstract
Studies on the determinants of oil palm farmers’ income have been widely conducted; however, analyses that specifically test the combined effects of land size, labor, and price within a single model in the local context of Pintas Tuo Village, Muara Tabir Subdistrict, remain limited. This study aimed to analyze the effects of land size (X1), labor (X2), and price (X3) on oil palm farmers’ income (Y). Using a quantitative approach with a field survey design, it involved 96 oil palm farmers determined using Slovin’s formula (10% margin of error) through a sampling procedure that combined purposive and simple random sampling. Data were collected through observation, structured interviews/questionnaires, and documentation, and were analyzed using multiple linear regression with classical assumption tests (normality, multicollinearity, heteroscedasticity). The results showed that land size (β = 0.293, p = 0.002), labor (β = 0.363, p < 0.001), and price (β = 0.299, p = 0.002) had positive and significant effects on income, both partially and simultaneously (F = 60.578, p < 0.001), with the model explaining 65.3% of the variance in income (adjusted R² = 0.653). These findings reinforce the production economics framework of farming enterprises, which posits that income is influenced by production inputs and market factors, and highlight the importance of strengthening labor management and strategies for dealing with price volatility. The study recommends that relevant stakeholders, including local government and farmer organizations, promote productivity intensification, improved work efficiency, and expanded access to market information, while future research is advised to incorporate variables such as production costs, productivity per hectare, and plant age to achieve a more comprehensive income model.
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