PUTRI, LISYA NABILA and Hanum, Herlina and Ngudiantoro, Ngudiantoro (2024) IMPLEMENTASI GENERALIZED TWO STAGE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS DAN AUTOKORELASI PADA INDONESIA SHARIA STOCK INDEX. Undergraduate thesis, Sriwijaya University.
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Abstract
Multiple linear regression analysis sometimes has multicollinearity and autocorrelation problems. The combination of Generalized Ridge Regression and Two Stage Least Square is one method used to overcome multicollinearity and autocorrelation problems. In this research, the combination of Generalized Ridge Regression and Two Stage Least Square is called Generalized Two Stage Ridge Regression. The results of the analysis show that there is a multicollinearity problem because the VIF value of the independent exchange rate variable USD and IDJ is above 5 and experiences a positive autocorrelation problem because the Durbin Watson value is 1,401 <d_L 1,494. The stages in this research are detecting data that experiences multicollinearity and autocorrelation problems, then estimating Generalized Ridge Regression, namely transforming the data using the centering and rescaling method, determining the k value, determining the Generalized Two Stage Ridge Regression equation, and transforming the Generalized Two Stage Ridge Regression equation. The results of the analysis using the Generalized Two Stage Ridge Regression method are that the VIF value for each independent variable is below 5 and the Durbin Watson value is 4 - d<d_L, so that the problems of multicollinearity and autocorrelation have been overcome.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Generalized Ridge Regression, 2SLS, Multikolinearitas, Autokorelasi |
Subjects: | Q Science > QA Mathematics > QA1-939 Mathematics > QA37.3.1.64 Applied Mathematics |
Divisions: | 08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1) |
Depositing User: | Lisya Nabila Putri |
Date Deposited: | 29 Mar 2024 01:00 |
Last Modified: | 29 Mar 2024 01:00 |
URI: | http://repository.unsri.ac.id/id/eprint/142983 |
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