Collection of stand parameter data has often not carried out thoroughly, including ignoring tree height measurements. Tree height has an important role to understand stand structure but it is difficult to do because of inadequate field conditions, limited availability of tools and methods as well as the skills of the individuals who measure them. The Purpose of this study was to build a model for estimating jati (Tectona gandis) height in community forests of Batupanga Daala Village, Luyo District, Polewali Mandar Regency, West Sulawesi Province. This research was conducted from January to May 2023. Data collection was carried out by measuring 70 trees in which 10 trees were obtained for each diameter class. The development of the high estimator model used five regression equations including those derived logarithmically and exponentially to estimate the dependent variable. The selection of the best model is based on four indicators, namely the coefficient of determination (R2), bias, error index, and Mean Square Error Prediction (MSEP). The results showed that the model with the highest score for estimating teak height in the Batupanga Daala Village community forest was Ŷ = 0.274X0.878 with an R² value of 0.881, bias = 0.845, error index = 77.39 and MSEP = 2.06. where Y is the estimated height and X is the diameter (DBH).
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