Application of Science, Technology, and Innovation in Forest Management

Aplikasi Pemanfaatan Ilmu Pengetahuan, Teknologi dan Inovasi  dalam Manajemen Hutan

Abstract

Traditional conservation is often hampered by significant challenges, including low accessibility to large protected areas, delayed responses to threats such as poaching and deforestation, and reliance on manual survey data that is costly, time-consuming, and prone to inaccuracy. These constraints lead to conservation decisions that are often subjective and lack empirical support. This study aims to systematically synthesize and analyze developments in Science, Technology, and Art/Innovation (Iptek) in forest protected area management, as well as evaluate their contribution to improving the effectiveness of evidence-based conservation management.  The research methodology uses a Systematic Literature Review (SLR) approach, which is qualitative-analytical in nature, where the main focus is to identify, evaluate, and synthesize the latest scientific findings from reputable databases (such as Scopus and Web of Science) regarding the application of Science and Technology (Iptek) in forest protected area management. The results of the study show that the integration of science and technology enables a transition from reactive management to predictive and proactive conservation. Science and technology provide a framework for Evidence-Based Conservation Management.  The use of Iptek has yielded measurable results in terms of increased conservation effectiveness. For example, the implementation of a spatial data-based patrol system, as implemented through the SMART Patrol initiative, has shown a success rate of up to 80% higher in detecting and preventing illegal activities compared to patrols without spatial data. On the other hand, camera trap data analysis using AI has been proven to be 99% faster in identifying wildlife than manual analysis, enabling a much faster conservation response to population changes. This efficiency also results in savings of 50-70% in survey costs and time through the use of drones and remote sensing.