Penggunaan Analisis Regresi Terboboti dalam Penyusunan Model Pertumbuhan Peninggi Acacia mangium Willd.
Abstract: The compilation of
growth stand model usually uses the regression analysis. Homoscedasticity or
residual kind homogeneity is one assumption which underlying the use of this
regression analysis. Breaking this assumption causes the low of model accuracy
which is shown by the low of determination coefficient and the height of error
standard. The problem of
heteroscedasticity can be solved by using weighted regression analysis.The
Selected Raiser Growth Model equation in this research was transformed into a
model equation: ln P = a + b/A, where there was a significant correlation
between the growth and the age (R2 = 55.04%, sb0=0.041, and sb1= 0.171). From
the use of weighted regression analysis with weightier wi= 1/”Xi, it can beconcluded
that there was no real correlation between the growth and the age (R2 = 0.55%,
sb0 = 0.572, and sb1= 2.560). The use of weightier shows much lower accuracy
than without weightier. However, from theuse of weighted regression analysis
with weightier: wi= 1/si2, where si2 = residual kinds at free variable group to
I(X1) shows that there was significant correlation between the growth and the
age (R2 = 45.46%; sb0 = 0.084,and sb1 = 0.205). There fore it can be said that
the accuracy was much better than regression without weightier.Furthermore, the
use of weighted regression analysis with weightier wi= 1/si2, where si2is
residual kind at free variable to i (X) which is estimated through second orde
polynomial regression model shows a very significant correlation between the
growth and the age (where R2 = 87.22%, sb0= 0.029, and sb1 = 0.072). Thelast
result shows a better accuracy than the preceding treatments. From this
research, it can be concluded that by using a suitable weightier, the use of
weighted regression analysis in compiling raiser grow th model can improve the
model accuracy.
Penulis: Muhdin dan
Endang Suhendang
Kode Jurnal: jpkehutanandd090075
