PEMODELAN JUMLAH UANG BEREDAR MENGGUNAKAN PARTIAL LEAST SQUARES REGRESSION (PLSR) DENGAN ALGORITMA NIPALS (NONLINEAR ITERATIVE PARTIAL LEAST SQUARES)

Published: 22 Jul 2015.
Open Access

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Abstract

Money supply has a tendency to increase or decrease the price level. Because of it, it is important to do a restraint and control action on money supply through its affecting factors include net foreign assets, net claims on central government, claims on region government, claims on the other finances institution, claims on nonfinances enterprise of state-owned corporation, and claims on private sector. In this study, a model has done between money supply and its affecting factors using Partial Least Squares Regression (PLSR) with NIPALS (Nonlinear Iterative Partial Least Squares) algorithm because the affecting factors of money supply data is detected multicollinearity. In the PLSR, regression coefficient is obtained iteratively. Three stage iteration process in PLSR produce weight vector, loading vector, and parameter estimation that produce PRESS and R2 values later. Based on the analysis, PLSR model to the money supply data in July 2012 until December 2014 is obtained at the fourth iteration with minimum PRESS value as 2,10815x1010. That PLSR model has R2 value as 99,47%, so it is very good for explaining the money supply. By means of bootstrap technique, concluded that all of the affecting factors of money supply on PLSR model influence money supply significantly.

 

Keywords: money supply, multicollinearity, PLSR, NIPALS

Keywords: money supply, multicollinearity, PLSR, NIPALS

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