PEMODELAN REGRESI NONPARAMETRIK SPLINE TRUNCATED PADA FAKTOR-FAKTOR YANG MEMPENGARUHI PERTUMBUHAN EKONOMI DI PROVINSI MALUKU - Muhammad Yahya Matdoan; A. M. Balami; M. W. Talakua (VARIANCE: Journal of Statistics and Its Applications, 2019)
Economic growth is a benchmark for the success of a region's development, especially in the economic field. The purpose of economic development in an area is basically to improve the welfare and prosperity of the community. Economic growth in Maluku Province experienced a positive increase. However, there is still a disparity between districts/cities in Maluku Province, which has an impact on increasing unemployment and an increasingly poor population. This is inseparable from the influencing factors so that it can be precisely done by modeling these factors using the truncated nonparametric spline regression method. the advantages of this method occur because in nonparametric spline truncated regression has knot points, which are joint fusion points that indicate changes in data behavior patterns. Besides, this method can be used to model data patterns that change at certain sub-intervals. The best model is very dependent on determining the optimal knot point by using the minimum Generalized Cross-Validation (GCV) value. The results obtained in this study were the highest percentage of economic growth in Maluku Province, Ambon City with a percentage of 6.17%, and the lowest economic growth was in the East Seram District (SBT) with a percentage of 5.03%. Furthermore, the best model is obtained with a model with three knots and a GCV value of 11.61, a value of 2 of 0.94 and an MSE value of 0.005. This means that statistically, the variables used in this study affect economic growth by 94%. While the rest is influenced by other variables outside the research.