Systematic Literature Review: Optimasi Keputusan Pada Monitoring Kesehatan Hutan Menggunakan Metode Multi-Objective Optimization By Ratio Analysis (MOORA) - Ari Andrianti; Willy Bima Alfajri; Miranty yudistira (Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas, 2026)
Forest health monitoring is a crucial component of sustainable forest management, particularly amid increasing pressures from deforestation, land degradation, and climate change. The complexity of forest ecosystems means that decision-making processes cannot rely on a single indicator but instead require approaches capable of simultaneously accommodating multiple biophysical, environmental, and social criteria. Therefore, Multi-Criteria Decision Making (MCDM) methods have been widely applied in decision support systems within the forestry sector. This study aims to systematically examine the application of the Multi-Objective Optimization by Ratio Analysis (MOORA) method in optimizing decision-making for forest and environmental health monitoring. The research adopts a Systematic Literature Review (SLR) methodology based on the PRISMA guidelines. The SLR process includes the formulation of research questions, literature search strategies, the establishment of inclusion and exclusion criteria, quality assessment of selected studies, and narrative synthesis of the findings. Literature searches were conducted using Google Scholar, Scopus, and OpenAlex databases, covering articles published between 2021 and 2026. The selection results indicate that the MOORA method has been extensively applied in environmental and natural resource decision support systems, particularly for alternative ranking and the determination of forest and land management priorities. Overall, MOORA is considered effective in producing objective, consistent, and easily interpretable decisions, either as a standalone method or in combination with other approaches such as AHP, ORESTE, and GIS. However, most existing studies remain case-based with limited geographical scope and have not yet developed standardized forest health indicators. These findings highlight opportunities for further research to develop more comprehensive MOORA-based forest health monitoring models to support environmental management and sustainable forest management policies.