<![CDATA[The forestry sector is a strategic sector in Indonesia characterized by high-risk work, remote locations, dependence on natural conditions, and demands for both physical and psychological resilience from employees. These conditions create an opportunity for employee resilience to serve as an intervening variable between organizational determinants—specifically transformational leadership, organizational support, and workload—and employee performance. This article aims to comprehensively demonstrate the model testing process using component-based Structural Equation Modeling (specifically, standardized regression as an approximation of PLS Path Modeling), while also presenting a methodologically developed research instrument and a field survey plan ready for implementation. As actual field data was unavailable during the article's preparation, all numerical results (n = 220) are derived from mathematically generated simulation data; the data structure is consistent with the hypothesized relationships (H1–H7) and reflects a demographic profile typical of the forestry sector based on secondary literature. The simulation results demonstrate that the analysis workflow—ranging from validity and reliability testing and path coefficient analysis to the Sobel test and Variance Accounted For (VAF) calculation—can be executed consistently, yielding relationship patterns that align with theoretical expectations: transformational leadership (β = 0.261) and organizational support (β = 0.284) positively influence employee resilience, whereas workload has a negative influence (β = -0.321); furthermore, employee resilience positively influences employee performance (β = 0.357) and mediates the effects of the three aforementioned determinants (VAF 36.9%–52.9%). As these figures are based on simulation, they do not represent the actual conditions of Industrial Forest Plantation (HTI) employees and cannot serve as a basis for policy decisions or empirical claims. The article's primary contribution lies in the validated, consistent analysis pipeline, alongside the research instrument and survey plan detailed in the supplementary documentation, which are ready for use in primary data collection for future research.]]>
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