38
Table 4.2 Companies Name List
No Companies Name Code
1 PT Astra Agro Lestari
AALI 2
PT Adhi Karya ADHI
3 PT AKR Corporindo
AKRA 4
PT Aneka Tambang ANTM
5 PT Astra International
ASII 6
PT Alam Sutera Realty ASRI
7 Bank BNI
BBNI 8
Bank BRI BBRI
9 Bank Danamon
BDMN 10
Bank Mandiri BMRI
11 PT Global Mediacom
BMTR 12
PT Bumi Serpong Damai BSDE
13 PT XL Axiata
EXCL 14
PT Indocement Tunggal Prakasa INTP
15 PT Jasa Marga
JSMR 16
PT Lippo Karawaci LPKR
17 PT Perusahaan Perkebunan London Sumatera
Indonesia LSIP
18 PT Media Nusantara Citra
MNCN 19
PT Bukit Asam PTBA
20 PT Pakuwon Jati
PWON 21
PT Telkom Indonesia TLKM
Source: www.idx.co.id
B. Analysis and Discussion
1. Descriptive Statistics
Research variables used in this study include Good corporate governance that consists of managerial ownership and independent commissioners, growth
opportunities and sales growth as an independent variable while the dependent variable is accounting conservatism. Descriptive statistical test result can be seen
in Table 4.3.
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Table 4.3 Descriptive Statistics Test Result
Descriptive Statistics
N Minimum
Maximum Mean
Std. Deviation Cons Y
84 10.00
50.20 22.0985
9.24824 indepent X1
84 .25
.67 .4179
.09946 Manag X2
84 .00
.50 .2726
.13340 GO X3
84 .13
9.94 2.6668
1.66203 SG X4
84 -.34
.57 .2311
.15034 Valid N listwise
84
Source: Data processed
Table 4.3 Shows the descriptive statistics for the independent variables and the dependent variable. Based on Table 4.3, the results of the analysis using
descriptive statistics of the Independent commissioner Indepent indicates the minimum value of 0.25 maximum value of 0.67 with an average of 0.4179 and a
standard deviation of 0.09946. In variable Managerial ownership Manag indicates the minimum value of 0, the maximum value of 0.50 with an average of
0.2726 and a standard deviation of 0.13340. Growth opportunities in the variable GO indicates the minimum value of 0.13 maximum value of 9.94 with an
average of 2.6668 and a standard deviation of 1.66203. Variable Sales Growth SG indicated a minimum value of -0.34, the maximum value of 0.57 with an
average of 0.2311 and a standard deviation of 0.15034 Whereas, Accounting conservatism Cons indicates a minimum value of 10, the maximum value of
50.20 with an average of 21.9770 and a standard deviation of 8.93653
40
2. The Result of Data Quality Test
a. The Result of Normality Test
Normality of the data was tested using the Kolmogorov-Smirnov Z with a significant level of 0.05. From the Kolmogorov-Smirnov test Z has
done Kolmogorov-Smirnov Z values of 0.996 and significant of 0.275 more than 0.05 means that it can be considered fulfilled normality test Sufren and
Natanael, 2014. Here is the data normality test results:
Table 4.4 Data Normality Test Results
One-Sample Kolmogorov-Smirnov Test
Unstandardized Residual
N 84
Normal Parameters
a,,b
Mean .0000000
Std. Deviation 7.77218021
Most Extreme Differences Absolute
.109 Positive
.109 Negative
-.045 Kolmogorov-Smirnov Z
.996 Asymp. Sig. 2-tailed
.275 a. Test distribution is Normal.
b. Calculated from data.
Source: Data Processed
b. The Result of Multicollinearity Test
Multicollinearity testing in this study conducted by looking at the value of collinearity statistics and the correlation coefficient between independent
variables. The test results shown in table 4.5
41
Table 4.5 Multicollinearity Test Results
Coefficients
a
Model Collinearity Statistics
Tolerance VIF
1 indepent
X1 .918
1.090 Manag X2
.950 1.053
GO X3 .961
1.041 SG X4
.942 1.062
Source: Data Processed Multicolinearity test aims to test whether the regression model found a
correlation between independent variables. A good regression model should not happen correlation between independent variables. Multikoloniaritas
occurs when 1 the value of tolerance Tolerance 0.10 and 2 variance inflation factor VIF 10. Based on Table 4.5 indicates VIF of Indepent,
manag, GO and SG is smaller than 10. Meanwhile, tolerancenya value greater than 0.10. This suggests that the independent variables in this study are not
correlated so that the model does not contain multicollinearity Sufren and Natanael, 2014.
c. The Result of Heteroscedasticity Test
Results heteroscedasticity in this study by looking at the scatterplot graph among other residue SDRESID dependent variables with independent
predictive value variable ZPRED. Detection of the presence or absence heterokedastisitas can be seen where Y is the residual value and the value of X
is the predicted value. The scatterplot graph can be seen from Figure 4.1
42
Based Scatterplot image above can be concluded that there is no clear pattern, as well as the points spread. Thus, the analysis model
can be concluded not happen heterocedastisity Sufren and Natanael, 2014.
d. The Result of Autocorrelation Test
Autocorrelation test is used to determine and detect the presence of autocorrelation. Autocorrelation in this research is using Durbin Watson. A
good model is a regression model that is free from autocorrelation. Autocorrelation test results shown in Table 4.6
Table 4.6
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Autocorrelation Test Results
Model Summary
b
Model R
R Square Adjusted R Square
Std. Error of the Estimate
Durbin-Watson 1
.542
a
.294 .258
7.96651 1.814
a. Predictors: Constant, SG X4, GO X3, Manag X2, indepent X1 b. Dependent Variable: Cons Y
Source: Data Processed
If the numbers Durbin Watson below -2 means there is positive autocorrelation, when between -2 to 2 means no autocorrelation, while more
than 2 means there is a negative autocorrelation. The results of data processing showed that D-W = 1.814. so that, there is no autocorrelation
Sufren and Natanael, 2014.
3. Hypothesis Testing
a. Coefficient of Determination R
2
Table 4.7 Coefficient Determination Test Results R
2
Model Summary
b
Model R
R Square Adjusted R Square
Std. Error of the Estimate
Durbin-Watson 1
.542
a
.294 .258
7.96651 1.814
a. Predictors: Constant, SG X4, GO X3, Manag X2, indepent X1 b. Dependent Variable: Cons Y
Source: Data Processed
The result of the calculation produces adjusted R-square is equal to 0.258 or 26 which demonstrates the ability Indepent, manag, GO and SG in
44
explaining the variations that occur in accounting conservatism by 26 while the remaining 74 is explained by other variables not examined in this study.
To avoid bias, the coefficient of determination used in this research is by using Adjusted R Square because it can go up or down if the independent variable is
added to the model. If the test Adjusted R Square obtained value is negative, then the value of Adjusted R Square is zero Kuncoro, 2009: 221.
b. Multiple Regression Analysis Result
Multiple regression analysis is used to describe the relationship of variables - independent variables are Indepent, Manag, GO and SG on the
dependent variable, namely Accounting conservatism. The results of multiple regression analysis are shown in Table 4.8:
Table 4.8 Multiple Regression Data Results
E s
t i
m a
Estimation Model : Y = 17.196 + -8.538X
1
+ -7.494X
2
+ 2.718X
3
+ 14.122X
4
+ e
Coefficients
a
Model Unstandardized Coefficients
Standardized Coefficients
T Sig.
B Std. Error
Beta 1
Constant 17.196
4.541 3.787
.000 indepent X1
-8.538 9.178
-.092 -.930
.355 Manag X2
-7.494 6.725
-.108 -1.114
.269 GO X3
2.718 .537
.489 5.064
.000 SG X4
14.122 5.994
.230 2.356
.021 a. Dependent Variable: Cons Y
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From the table above it can be seen that the value of the constant is 17.196, Indepent coefficient of -8.538, Manag coefficient of -7.494, GO
coefficient of 2.718, the coefficient SG amounted to 14.122. α 17.196, This means that if the independent variable managerial ownership,
indepedent commissioner, growth opportunities and sales growth is zero, then the dependent variable accounting conservatism will be worth 17.196 units.
β -8.538, means that if the Independent Commissioner variable increases by one unit and the other variables constant, the dependent variable is the
accounting conservatism will be decreased 8.538units. β -7.494, This means that if the variable Managerial Ownership increased by
one unit and the other variables constant, the dependent variable is the accounting conservatism will decrease 7.494units.
β 2.718, This means that if the variable Growth Opportunities increased by one unit and the other variables constant, the dependent variable is the
accounting conservatism will increase 2.718 units
.
β 14.122, This means that if the variable Growth Sales increased by one unit and the other variables constant, the dependent variable is the accounting
conservatism will increase 14.122 units.
The following are the test results of individual parameter significance of each independent variable on the dependent variable:
1. Independent commissioner
46
See table 4.8 regression coefficient of -8.538 and Tcount value of -0.930 with a significant value of 0.355
greater than α 0.05, then it can be concluded that the Independent commissioner has no effect on accounting conservatism
Sufren and Natanael, 2014. 2. Managerial Ownership
See table 4.8 regression coefficient of -7.494and Tcount value of -1.114 with a significant value of 0.269
greater than α 0.05, then we can conclude that managerial ownership has no effect on accounting conservatism Sufren and
Natanael, 2014. 3. Growth Opportunities
See table 4.8 regression coefficient of 2.718 and the value Tcount of 5.064 with significant value of 0.000 smaller than α 0.05, then it can be concluded
that growth opportunities has effect on accounting conservatism Sufren and Natanael, 2014.
4. Sales Growth See table 4.8 regression coefficient of 14.122 and Tcount of 2.356 with
significant value of 0,021 is smaller than α 0.05, then it can be concluded
that the sales growth has effect on accounting conservatism Sufren and Natanael, 2014
c. Significant Partial Test T-Test
1. The effect of Independent commissioner to Accounting conservatism
47
This study aimed to test the existence of an independent commissioner to accounting conservatism. Tcount of -0.930 with a
significant value of 0.355
greater than α 0.05 so it can be stated that H1 Rejected
Sufren and Natanael, 2014. Because the commissioner independent variables showed a negative effect on the accounting
conservatism and different result with the beginning hypotesis. This is because the proportion of independent directors on the company LQ 45
listing on the Stock Exchange during the observation period is still low. Seen on the descriptive statistical analysis results average value that is
equal to 0.4179. It shows that the most sampled companies still have number of
independent directors in the range of a minimum average of 40 a little more than what has been required by Bapepam as much as 30. The low
proportion of independent commissioners in this study suggests that the monitoring activity undertaken by independent directors in a company is
not optimally used as a tool to monitor management. The existence and the appointment of independent board is done just to meet the regulations
could be the cause of an independent commissioner does not have a
significant effect. Research in support of research conducted by Padmawati and Fachrurrozie 2015 were unable to prove the influence of
independent directors on accounting conservatism. The results of this study different from the results of research
Rahmawati 2010 where the research results show that the independence of commissioners has a significant influence on accounting conservatism
as measured by the size of the accrual. The difference is because the
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research results in research Rahmawati 2010 uses a manufacturing company as a sample and measurement using measurement accrual
accounting
2. The effect of Managerial Ownership to Accounting Conservatism
