Effectiveness of Social Forestry Programs in Improving Community Welfare: A Quantitative Analysis
DOI:
https://doi.org/10.62872/jh.v1i2.570Keywords:
social forestry, community welfare, multiple linear regressionAbstract
Social forestry programs in Indonesia have been implemented to improve the welfare of communities living within and around state forest areas. Despite a national target of 12.7 million hectares allocated for community management, empirical evidence on the determinants of welfare outcomes remains fragmented. This quantitative study examines the effect of five independent variables—income contribution from social forestry (X1), institutional capacity of farmer groups (X2), technical accompaniment (X3), market access (X4), and land tenure security (X5)—on community welfare (Y) among social forestry permit holders in selected sites across Indonesia. Data were collected through structured questionnaires administered to 120 respondents from active kelompok tani hutan (KTH) across five study sites in East Java, West Nusa Tenggara, NTT, and Sulawesi. Instruments were validated through Pearson validity testing and reliability testing using Cronbach's alpha (α > 0.70 for all constructs). Data were analyzed using IBM SPSS Statistics 26 through descriptive statistics, Pearson correlation analysis, and multiple linear regression. Results indicate that all five independent variables are significantly and positively correlated with community welfare. Multiple regression analysis yields an Adjusted R² of 0.596, indicating that the five variables together explain 59.6% of variance in community welfare. Income contribution (β = 0.312, p < 0.001) and technical accompaniment (β = 0.272, p < 0.001) emerge as the strongest predictors. Institutional capacity (β = 0.236, p < 0.001), market access (β = 0.193, p = 0.003), and land tenure security (β = 0.141, p = 0.027) also significantly predict welfare outcomes.
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