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LAMPIRAN TABEL DAN STATISTIK

OUTPUT SPSS

Laba dan Arus Kas terhadap Laba pada Perusahaan Konservatif

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Case Processing Summary

CasesValid Missing Total

N Percent N Percent N PercentUnstandardized Residual 226 71.7% 89 28.3% 315 100.0%

Descriptives

Statistic Std. ErrorMean .0000029 1112818708.48

Lower Bound -2192879806.9695% ConfidenceInterval for Mean Upper Bound

2192879806.96

5% Trimmed Mean -41615080.28Median 442292191.91Variance 2.799E+020Std. Deviation 16729333459.99Minimum 3.7457E+010Maximum 43878888164Range 81336131208.26Interquartile Range 20093542355.62Skewness .014 .162

UnstandardizedResidual

Kurtosis -.074 .322

Extreme Values

Case Number Value1 290 438788881642 86 420119391863 22 415785626294 85 40174317666

Highest

5 32 337554580951 294 3.7457E+0102 141 3.6812E+0103 55 3.6341E+0104 121 3.5128E+010

Unstandardized Residual

Lowest

5 44 3.4933E+010

Tests of Normality

Kolmogorov-Smirnov(a) Shapiro-WilkStatistic df Sig. Statistic df Sig.

Unstandardized Residual .058 226 .062 .990 226 .128a Lilliefors Significance Correction

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: E_t

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error of theEstimate

Durbin-Watson

1 .997(a) .994 .994 16804185437.6 2.071a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

ANOVA(b)

ModelSum ofSquares df Mean Square F Sig.

Regression 1.056E+025 2 5.282E+024 18705.333 .000(a)Residual 6.297E+022 223 2.824E+020

1

Total 1.063E+025 225a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficients

CollinearityStatisticsModel

B Std. Error Betat Sig.

Tolerance VIF(Constant) -1740961859 1201563919 -1.449 .149E_t0 .726 .013 .652 54.238 .000 .184 5.446

1

CFO_t0 .327 .011 .368 30.554 .000 .184 5.446a Dependent Variable: E_t

Coefficient Correlations(a)

Model CFO_t0 E_t0Correlations CFO_t0 1.000 -.904

E_t0 -.904 1.000Covariances CFO_t0 .000 .000

1

E_t0 .000 .000a Dependent Variable: E_t

Collinearity Diagnostics(a)

Variance ProportionsModel Dimension Eigenvalue

ConditionIndex

(Constant) E_t0 CFO_t01 1.972 1.000 .03 .04 .042 .936 1.451 .85 .01 .00

1

3 .091 4.647 .12 .94 .96a Dependent Variable: E_t

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value -518465716224 2419476660224 36879680901.46 216682545906.374 226Std. Predicted Value -2.563 10.996 .000 1.000 226Standard Error ofPredicted Value

1117883392 12921582592 1431167237.667 1306802341.622 226

Adjusted PredictedValue

-527779069952 2394818871296 36696640894.26 215580452688.896 226

Residual -37457244160 43878887424 .000 16729333459.990 226Std. Residual -2.229 2.611 .000 .996 226Stud. Residual -2.240 2.619 .004 1.004 226Deleted Residual -37837750272 44146802688 183040007.201 17102863202.861 226Stud. DeletedResidual

-2.261 2.654 .005 1.008 226

Mahal. Distance .000 132.043 1.991 13.148 226Cook's Distance .000 1.214 .009 .082 226Centered LeverageValue

.000 .587 .009 .058 226

a Dependent Variable: E_t

Uji Glejser

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: AbsUt

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error ofthe Estimate

1 .122(a) .015 .006 1.060E+010a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

ANOVA(b)

Model Sum of Squares dfMeanSquare F Sig.

Regression 3.802E+020 2 1.901E+020 1.691 .187Residual 2.507E+022 223 1.124E+020

1

Total 2.545E+022 225a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

Coefficients(a)

UnstandardizedCoefficients

StandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) 12374442657 758115348 16.323 .000E_t0 -.012 .008 -.217 -1.400 .163

1

CFO_t0 .012 .007 .275 1.776 .077a Dependent Variable: AbsUt

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value 11447308288 23930515456 12885279100.8256 1299893139.26018 226Residual -15856116736 31740641280 .00000 10555214131.84759 226Std. Predicted Value -1.106 8.497 .000 1.000 226Std. Residual -1.496 2.994 .000 .996 226

a Dependent Variable: AbsUt

Descriptives

Descriptive Statistics

N Minimum Maximum Mean Std. DeviationE_t0 226 -792946330000 2039938000000 23537319670.79 195187429505.214CFO_t0 226 -132642000000 2871554000000 65794217963.25 244183125051.584E_t 226 -509864290000 2436521000000 36879680901.46 217327394266.078Valid N (listwise) 226

Laba dan Arus Kas terhadap Laba pada Perusahaan Non-

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Case Processing Summary

CasesValid Missing Total

N Percent N Percent N PercentUnstandardized Residual 50 64.9% 27 35.1% 77 100.0%

Descriptives

Statistic Std. ErrorMean -.0000130 1644352676.5013

Lower Bound -3304450419.803666095% ConfidenceInterval for Mean Upper Bound

3304450419.8036410

5% Trimmed Mean -167927163.4757948Median -359185664.8975635Variance 1.352E+020Std. Deviation 11627329282.16319000Minimum 2.7171E+010Maximum 31968913546Range 59139972461.21260Interquartile Range 12866440143.62782Skewness .205 .337

UnstandardizedResidual

Kurtosis .704 .662

Extreme Values

Case Number Value1 45 319689135462 54 250924850673 72 207053192244 2 16546766732

Highest

5 70 143693743781 38 2.7171E+0102 8 2.3453E+0103 34 1.8467E+0104 16 1.6811E+010

UnstandardizedResidual

Lowest

5 43 1.6446E+010

Tests of Normality

Kolmogorov-Smirnov(a) Shapiro-WilkStatistic df Sig. Statistic df Sig.

UnstandardizedResidual

.118 50 .079 .979 50 .509

a Lilliefors Significance Correction

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: E_t

Model Summary(b)

Model R R SquareAdjusted R

SquareStd. Error of the

EstimateDurbin-Watson

1 1.000 .999 .999 11872142008.210 1.821a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

ANOVA(b)

ModelSum ofSquares df Mean Square F Sig.

Regression 1.239E+025 2 6.197E+024 43964.882 .000Residual 6.625E+021 47 1.409E+020

1

Total 1.240E+025 49a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficients

CollinearityStatisticsModel

B Std. Error Betat Sig.

Tolerance VIF(Constant) -1123812807 1831095494 -.614 .542E_t0 1.376 .011 .941 123.731 .000 .196 5.094

1

CFO_t0 .098 .012 .065 8.477 .000 .196 5.094a Dependent Variable: E_t

Coefficient Correlations(a)

Model CFO_t0 E_t0Correlations CFO_t0 1.000 -.896

E_t0 -.896 1.000Covariances CFO_t0 .000 .000

1

E_t0 .000 .000a Dependent Variable: E_t

Collinearity Diagnostics(a)

Variance ProportionsModel Dimension Eigenvalue

ConditionIndex

(Constant) E_t0 CFO_t01 1.901 1.000 .01 .05 .052 1.000 1.379 .80 .00 .01

1

3 .100 4.368 .19 .95 .94a Dependent Variable: E_t

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value -29252831232 3554004172800 89463311414.59 502920103351.993 50Std. Predicted Value -.236 6.889 .000 1.000 50Standard Error ofPredicted Value

1697962496 11804088320 2203101385.725 1917483905.157 50

Adjusted PredictedValue

-13570622464 3252468580352 83896616547.81 460460995026.077 50

Residual -27171059712 31968913408 .000 11627329282.164 50Std. Residual -2.289 2.693 .000 .979 50Stud. Residual -2.312 2.747 .038 1.070 50Deleted Residual -27739480064 305022402560 5566694866.772 44972415325.761 50Stud. DeletedResidual

-2.430 2.966 .045 1.107 50

Mahal. Distance .022 47.460 1.960 8.785 50Cook's Distance .000 217.516 4.387 30.757 50Centered LeverageValue

.000 .969 .040 .179 50

a Dependent Variable: E_t

Uji Glejser

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: AbsUt

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error ofthe Estimate

1 .067 (a) .005 -.038 8087921338a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.Regression 1.404E+019 2 7.020E+018 .107 .898Residual 3.074E+021 47 6.541E+019

1

Total 3.089E+021 49a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) 8589388396 1247437599 6.886 .000E_t0 -.003 .008 -.119 -.361 .720

1

CFO_t0 .002 .008 .064 .195 .846a Dependent Variable: AbsUt

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value 5096071168 8587965440 8409548172.9663 535272923.90613 50Residual -8400857600 23406200832 .00000 7921142161.29699 50Std. Predicted Value -6.190 .333 .000 1.000 50Std. Residual -1.039 2.894 .000 .979 50

a Dependent Variable: AbsUt

Descriptives

Descriptive Statistics

N Minimum Maximum Mean Std. DeviationE_t0 50 -4565702967 2436521000000 65822033426.60 344190537935.342CFO_t0 50 -955991716061 2058731000000 125511844.94 330147688420.324E_t 50 -32862170048 3557491000000 89463311414.58 503054495200.883Valid N (listwise) 50

Laba dan Arus Kas terhadap Arus Kas pada Perusahaan

Konservatif

ExploreCase Processing Summary

CasesValid Missing Total

N Percent N Percent N PercentUnstandardizedResidual

163 51.7% 152 48.3% 315 100.0%

Descriptives

Statistic Std. ErrorMean -.0000060 1022982153.47

LowerBound

-2020099007.1895% ConfidenceInterval for Mean

UpperBound

2020099007.18

5% Trimmed Mean 53622323.79Median -1832724495.23Variance 1.706E+020Std. Deviation 13060561828.31Minimum -2.8275E+10Maximum 27755811185Range 56030489410.72Interquartile Range 16375314988.94Skewness .132 .190

UnstandardizedResidual

Kurtosis -.365 .378

Extreme Values

Case Number Value1 103 277558111852 199 266828743283 138 260536409734 9 25243331971

Highest

5 309 244920912941 66 -2.8275E+102 113 -2.8054E+103 18 -2.8026E+104 251 -2.6483E+10

UnstandardizedResidual

Lowest

5 53 -2.6174E+10

Tests of Normality

Kolmogorov-Smirnov(a) Shapiro-WilkStatistic df Sig. Statistic df Sig.

UnstandardizedResidual

.062 163 .200 .979 163 .015

a Lilliefors Significance Correction

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: CFO_t

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error of theEstimate

Durbin-Watson

1 .960 .922 .921 13141936832.594 1.791a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

ANOVA(b)

ModelSum ofSquares df Mean Square F Sig.

Regression 3.273E+23 2 1.637E+23 947.575 .000Residual 2.763E+22 160 1.727E+20

1

Total 3.549E+23 162a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficients

CollinearityStatisticsModel

B Std. Error Betat Sig.

Tolerance VIF(Constant) 2829853178 1185628465 2.387 .018E_t0 .024 .011 .053 2.310 .022 .916 1.092

1

CFO_t0 .762 .019 .943 40.932 .000 .916 1.092a Dependent Variable: CFO_t

Coefficient Correlations(a)

Model CFO_t0 E_t0Correlations CFO_t0 1.000 -.290

E_t0 -.290 1.000Covariances CFO_t0 .000 .000

1

E_t0 .000 .000a Dependent Variable: CFO_t

Collinearity Diagnostics(a)

Variance ProportionsModel Dimension Eigenvalue

ConditionIndex

(Constant) E_t0 CFO_t01 1.474 1.000 .22 .02 .262 1.070 1.174 .12 .70 .01

1

3 .456 1.799 .66 .28 .73a Dependent Variable: CFO_t

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value -101118115840 241703927808 25184057882.61 44949382682.398 163Std. Predicted Value -2.810 4.817 .000 1.000 163Standard Error ofPredicted Value

1033039552 9530763264 1482794544.988 993021098.467 163

Adjusted PredictedValue

-99975708672 245058568192 25244794174.52 45199910767.439 163

Residual -28274677760 27755810816 .000 13060561828.306 163Std. Residual -2.151 2.112 .000 .994 163Stud. Residual -2.196 2.121 -.002 1.004 163Deleted Residual -29685624832 28000434176 -60736291.904 13337657495.259 163Stud. DeletedResidual

-2.223 2.145 -.002 1.009 163

Mahal. Distance .007 84.208 1.988 7.758 163Cook's Distance .000 .203 .008 .023 163Centered LeverageValue

.000 .520 .012 .048 163

a Dependent Variable: CFO_t

Uji Glejser

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: AbsUt

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error of theEstimate

1 .063 .004 -.009 7813104679.80854a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

ANOVA(b)

ModelSum ofSquares df

MeanSquare F Sig.

Regression 3.867E+19 2 1.934E+19 .317 .729Residual 9.767E+21 160 6.104E+19

1

Total 9.806E+21 162a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

Coefficients(a)

UnstandardizedCoefficients

StandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) 10237884973 704876262 14.524E_t0 .001 .006 .013 .159 .874

1

CFO_t0 .008 .011 .058 .700 .485a Dependent Variable: AbsUt

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value 9091390464 12847401984 10458176534.5921 488575897.29047 163Residual -10720259072 18962495488 .00000 7764725857.49939 163Std. Predicted Value -2.797 4.890 .000 1.000 163Std. Residual -1.372 2.427 .000 .994 163

a Dependent Variable: AbsUt

Descriptives

Descriptive Statistics

N Minimum Maximum Mean Std. DeviationE_t0 163 -792946330000 304092211853 -9429633932.10 102305138927.493CFO_t0 163 -132642000000 306964339000 29646447585.88 57974093640.599CFO_t 163 -129172000000 234892877849 25184057882.61 46808388978.897Valid N (listwise) 163

Laba dan Arus Kas terhadap Arus Kas pada Perusahaan Non-

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Case Processing Summary

CasesValid Missing Total

N Percent N Percent N PercentUnstandardizedResidual

54 70.1% 23 29.9% 77 100.0%

Descriptives

Statistic Std. ErrorMean -.0000147 4223463761.67

LowerBound

-8471195526.3463895% ConfidenceInterval for Mean

UpperBound

8471195526.34635

5% Trimmed Mean -51057561.0025088Median 4472652803.0477690Variance 9.632E+020Std. Deviation 31035993489.71102Minimum 7.1661E+010Maximum 74137373934Range 145797889247.87360Interquartile Range 31894138583.45307Skewness -.076 .325

UnstandardizedResidual

Kurtosis .573 .639

Extreme Values

CaseNumber Value

1 13 74137373934

2 46 722453925823 38 593389583624 27 41890192280

Highest

5 45 409690176111 43 7.1661E+0102 21 6.9945E+0103 67 6.2618E+0104 23 5.2426E+010

UnstandardizedResidual

Lowest

5 61 4.0299E+010

Tests of Normality

Kolmogorov-Smirnov(a) Shapiro-WilkStatistic df Sig. Statistic df Sig.

UnstandardizedResidual

.116 54 .068 .969 54 .179

a Lilliefors Significance Correction

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: CFO_t

Model Summary(b)

Model RR

SquareAdjustedR Square

Std. Error of theEstimate

Durbin-Watson

1 1.000 .999 .999 31638690408.928 1.745a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.Regression 9.060E+025 2 4.530E+025 45254.254 .000Residual 5.105E+022 51 1.001E+021

1

Total 9.065E+025 53a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficients

CollinearityStatisticsModel

B Std. Error Betat Sig.

Tolerance VIF(Constant) -7721184295 4449803793 -1.735 .089E_t0 1.390 .013 .972 104.455 .000 .127 7.848

1

CFO_t0 .086 .027 .029 3.140 .003 .127 7.848a Dependent Variable: CFO_t

Coefficient Correlations(a)

Model CFO_t0 E_t0Correlations CFO_t0 1.000 -.934

E_t0 -.934 1.000Covariances CFO_t0 .001 .000

1

E_t0 .000 .000a Dependent Variable: CFO_t

Collinearity Diagnostics(a)

Variance ProportionsModel Dimension Eigenvalue

ConditionIndex

(Constant) E_t0 CFO_t01 1.988 1.000 .02 .03 .032 .948 1.448 .93 .00 .01

1

3 .064 5.580 .04 .97 .97a Dependent Variable: CFO_t

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value -59206000640 9008873209856 252795906512.82 1307450540716.013 54Std. Predicted Value -.239 6.697 .000 1.000 54Standard Error ofPredicted Value

4366469632 31221450752 5625739913.755 4941119182.684 54

Adjusted PredictedValue

-60701745152 8592841768960 246919878388.70 1259803109826.753 54

Residual -71660511232 74137370624 .000 31035993489.712 54Std. Residual -2.265 2.343 .000 .981 54Stud. Residual -2.287 2.367 .017 1.052 54Deleted Residual -111624454144 427225284608 5876028124.118 68202656989.352 54Stud. DeletedResidual

-2.391 2.484 .018 1.079 54

Mahal. Distance .028 50.630 1.963 9.003 54Cook's Distance .000 59.187 1.170 8.058 54Centered LeverageValue

.001 .955 .037 .170 54

a Dependent Variable: CFO_t

Uji Glejser

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: AbsUt

Model Summary(b)

Model RR

SquareAdjustedR Square

Std. Error ofthe Estimate

1 .161 .026 -.012 2.058E+010a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.Regression 5.748E+020 2 2.874E+020 .679 .512Residual 2.160E+022 51 4.236E+020

1

Total 2.218E+022 53a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: AbsUt

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) 22967383846 2894595252 7.935 .000E_t0 .007 .009 .294 .759 .451

1

CFO_t0 -.018 .018 -.397 -1.024 .311a Dependent Variable: AbsUt

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation NPredicted Value 1472598400 28461510656 23123729485.2381 3293261992.73114 54Residual -22926182400 50348347392 .00000 20188899010.46564 54Std. Predicted Value -6.574 1.621 .000 1.000 54Std. Residual -1.114 2.446 .000 .981 54

a Dependent Variable: AbsUt

Descriptives

Descriptive Statistics

N Minimum Maximum Mean Std. DeviationE_t0 54 -33505297439 6332973000000 183845055847.39 914805324686.700CFO_t0 54 -292796988665 2482997000000 57716620403.50 445351692016.105CFO_t 54 -61446650211 9020067000000 252795906512.81 1307818851871.500Valid N (listwise) 54

HASIL REGRESI

Laba dan Arus Kas terhadap Laba pada Perusahaan Konservatif

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: E_t

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error of theEstimate

1 .997(a) .994 .994 16804185437.6a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

ANOVA(b)

ModelSum ofSquares df Mean Square F Sig.

Regression 1.056E+025 2 5.282E+024 18705.333 .000(a)Residual 6.297E+022 223 2.824E+020

1

Total 1.063E+025 225a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) -1740961859 1201563919 -1.449 .149E_t0 .726 .013 .652 54.238 .000

1

CFO_t0 .327 .011 .368 30.554 .000a Dependent Variable: E_t

Laba dan Arus Kas terhadap Laba pada Perusahaan Non-

Konservatif

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: E_t

Model Summary(b)

Model R R SquareAdjusted R

SquareStd. Error of the

Estimate1 1.000 .999 .999 11872142008.210

a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

ANOVA(b)

ModelSum ofSquares df Mean Square F Sig.

Regression 1.239E+025 2 6.197E+024 43964.882 .000Residual 6.625E+021 47 1.409E+020

1

Total 1.240E+025 49a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: E_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) -1123812807 1831095494 -.614 .542E_t0 1.376 .011 .941 123.731 .000

1

CFO_t0 .098 .012 .065 8.477 .000a Dependent Variable: E_t

Laba dan Arus Kas terhadap Arus Kas pada Perusahaan

Konservatif

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: CFO_t

Model Summary(b)

Model R R SquareAdjustedR Square

Std. Error of theEstimate

1 .960 .922 .921 13141936832.594a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

ANOVA(b)

ModelSum ofSquares df Mean Square F Sig.

Regression 3.273E+23 2 1.637E+23 947.575 .000Residual 2.763E+22 160 1.727E+20

1

Total 3.549E+23 162a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) 2829853178 1185628465 2.387 .018E_t0 .024 .011 .053 2.310 .022

1

CFO_t0 .762 .019 .943 40.932 .000a Dependent Variable: CFO_t

Laba dan Arus Kas terhadap Arus Kas pada Perusahaan Non-

Konservatif

Regression

Variables Entered/Removed(b)

ModelVariablesEntered

VariablesRemoved Method

1 CFO_t0,E_t0(a)

. Enter

a All requested variables entered.b Dependent Variable: CFO_t

Model Summary(b)

Model RR

SquareAdjustedR Square

Std. Error of theEstimate

1 1.000 .999 .999 31638690408.928a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.Regression 9.060E+025 2 4.530E+025 45254.254 .000Residual 5.105E+022 51 1.001E+021

1

Total 9.065E+025 53a Predictors: (Constant), CFO_t0, E_t0b Dependent Variable: CFO_t

Coefficients(a)

Unstandardized CoefficientsStandardizedCoefficientsModel

B Std. Error Betat Sig.

(Constant) -7721184295 4449803793 -1.735 .089E_t0 1.390 .013 .972 104.455 .000

1

CFO_t0 .086 .027 .029 3.140 .003a Dependent Variable: CFO_t