Application of Principal Component Analysis (PCA) to Reduce Multicollinearity Exchange Rate Currency of Some Countries in Asia Period 2004-2014 | Zendy

S.Fis. Umi Budi Rahayu | Zendy; Teguh Sugiarto | Zendy; Ludiro Madu | Zendy; Holiawati Holiawati | Zendy; Ahmad Subagyo | Zendy

Open Access

Application of Principal Component Analysis (PCA) to Reduce Multicollinearity Exchange Rate Currency of Some Countries in Asia Period 2004-2014

Author(s) -

S.Fis. Umi Budi Rahayu,

Teguh Sugiarto,

Ludiro Madu,

Holiawati Holiawati,

Ahmad Subagyo

Publication year - 2017

Publication title -

international journal of educational methodology

Language(s) - English

Resource type - Journals

ISSN - 2469-9632

DOI - 10.12973/ijem.3.2.75

Subject(s) - multicollinearity , principal component analysis , currency , exchange rate , liberian dollar , econometrics , yield (engineering) , us dollar , regression analysis , statistics , variance inflation factor , economics , mathematics , monetary economics , finance , materials science , metallurgy

This study aims to apply the model Principal component Analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hongkong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield levels of multicolinierity which is smaller in comparison with PCA applications using multiple regression. This study used multiple regression test and PCA application to investigate the differences in multicollinearity at yield. From this research, it can be concluded that the use of PCA analysis applications can reduce multicollinearity in variables in doing research.

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