PEMODELAN KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT MENGGUNAKAN REGRESI NONPARAMETRIK CAMPURAN KERNEL DAN SPLINE - Khansa Amalia Fitroh; Rukun Santoso; Suparti Suparti (Jurnal Gaussian, 2022)
Exchange currency is one way for a country to be able to transact with the outside world. Fluctuating movement of the rupiah exchange currency was caused by many influencing factors, such as exports, imports, the money supply (JUB), inflation, and JCI. To find out the relationship, nonparametric regression modeling was carried out with a mixed kernel estimator and a multivariable truncated linear spline. Import variables were approached with kernel regression because the data patterns were random and spread out while the export variables, JUB, inflation, and the Jakarta Composite Index (JCI) were approached with spline regression because the data patterns changed at certain sub-intervals. The purpose of this study is to model exchange currency of the rupiah against the US dollar with a mixed kernel and spline truncated estimator. The parameter estimation method used is Ordinary Least Square (OLS). The multivariable linear truncated spline and kernel mix estimator depends on knot points and bandwidth. The best model is seen from the knot point and optimal bandwidth obtained by selecting the minimum Generalized Cross Validation (GCV). The best model is applied to data on the exchange currency of the rupiah against the US dollar with two optimal knot points resulting in value of 0.7627. The model performance evaluation was calculated using MAPE and the resulting MAPE value was 0.598%.