Pengujian pada Regresi Ridge dan Penerapannya terhadap Data Produk Domestik Regional Bruto Provinsi Jawa Barat

Weni Nuryati, Suliadi Suliadi
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Abstract

Abstract. Ridge regression is one of the methods used to stabilize the value of the regression coefficient caused by multicollinearity. In ridge regression,  to reduce the impact of multicollinearity is carried out by adding ridge  parameter c to the hat matrix. This ridge parameter makes the regression coefficients have a smaller variance than the least squares method estimator variance. However, the ridge estimates are biased. Thus, hypothesis testing using the usual method cannot be applied to the coefficients ridge regression. Therefore Bae, et al., (2014) developed a method for testing the hypothesis of the coefficients of ridge regression. This thesis aims to apply this method to the gross regional domestic product data for West Java province in 2022. Based on the results of the research, it shows that there is a multicollinearity problem in the data, so it is modelLed using ridge regression. it was obtained The ridge regression model : . From the results of testing the hypothesis, it can be concluded that the independent variables, namely local original income (X1), general allocation funds (X2), profit sharing funds (X3), regional expenditures (X4) and labor (X5) together have a significant effect on the PDRB (Y) of West Java Province in 2022. The ridge regression model is returned to the original model . Abstract. Ridge regression is one of the methods used to stabilize the value of the regression coefficient caused by multicollinearity. In ridge regression,  to reduce the impact of multicollinearity is carried out by adding ridge  parameter c to the hat matrix. This ridge parameter makes the regression coefficients have a smaller variance than the least squares method estimator variance. However, the ridge estimates are biased. Thus, hypothesis testing using the usual method cannot be applied to the coefficients ridge regression. Therefore Bae, et al., (2014) developed a method for testing the hypothesis of the coefficients of ridge regression. This thesis aims to apply this method to the gross regional domestic product data for West Java province in 2022. Based on the results of the research, it shows that there is a multicollinearity problem in the data, so it is modelLed using ridge regression. it was obtained The ridge regression model : . From the results of testing the hypothesis, it can be concluded that the independent variables, namely local original income (X1), general allocation funds (X2), profit sharing funds (X3), regional expenditures (X4) and labor (X5) together have a significant effect on the PDRB (Y) of West Java Province in 2022. The ridge regression model is returned to the original model .
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摘要。脊回归是稳定多重共线性引起的回归系数值的方法之一。在脊回归中,通过在帽矩阵中加入脊参数c来减小多重共线性的影响。该脊形参数使回归系数的方差小于最小二乘法估计方差。然而,山脊估计是有偏差的。因此,通常的假设检验方法不能应用于系数岭回归。因此,Bae等人(2014)开发了一种检验岭回归系数假设的方法。本文旨在将该方法应用于2022年西爪哇省的区域生产总值数据。研究结果表明,该数据存在多重共线性问题,因此采用脊回归对其进行建模。得到脊回归模型:。从检验假设的结果可以看出,地方原始收入(X1)、一般分配资金(X2)、利润分成资金(X3)、区域支出(X4)和劳动力(X5)等自变量共同对2022年西爪哇省的PDRB (Y)有显著影响。脊回归模型回归到原模型。摘要。脊回归是稳定多重共线性引起的回归系数值的方法之一。在脊回归中,通过在帽矩阵中加入脊参数c来减小多重共线性的影响。该脊形参数使回归系数的方差小于最小二乘法估计方差。然而,山脊估计是有偏差的。因此,通常的假设检验方法不能应用于系数岭回归。因此,Bae等人(2014)开发了一种检验岭回归系数假设的方法。本文旨在将该方法应用于2022年西爪哇省的区域生产总值数据。研究结果表明,该数据存在多重共线性问题,因此采用脊回归对其进行建模。得到脊回归模型:。从检验假设的结果可以看出,地方原始收入(X1)、一般分配资金(X2)、利润分成资金(X3)、区域支出(X4)和劳动力(X5)等自变量共同对2022年西爪哇省的PDRB (Y)有显著影响。脊回归模型回归到原模型。
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