LAMPIRAN 1 INPUT DATA TIAP VARIABEL

(1)

LAMPIRAN 1

(2)

(3)

(4)

(5)

LAMPIRAN 2

OUTPUT DATA

UJI ASUMSI KLASIK DAN

(6)

UJI ASUMSI KLASIK PENGHITUNGAN MANAJEMEN LABA

UJI NORMALITAS (SEBELUM DATA NORMAL)

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Unstandardized Residual 89 100.0% 0 .0% 89 100.0%

Descriptives

Statistic Std. Error

Unstandardized Residual Mean

- 9.7358919E-18

.01147039

95% Confidence Interval for Mean

Lower Bound

- 2.2794995E-2

Upper Bound .0227950

5% Trimmed Mean _.0048805

Median _.0060332

Variance _.012

Std. Deviation _.10821147

Minimum -.47805

Maximum _.30414

Range _.78219

Interquartile Range _.09055

Skewness -1.125 .255

Kurtosis 5.126 .506

M-Estimators

Huber's M-Estimatora

Tukey's Biweightb

Hampel's

M-Estimatorc Andrews' Waved

Unstandardized Residual .0043159 .0042943 .0056681 .0041480

a. The weighting constant is 1.339. b. The weighting constant is 4.685.

(7)

Percentiles

Percentiles

5 10 25 50 75 90 95

Weighted Average(Defi nition 1)

Unstandard ized Residual

-Tukey's Hinges

-Extreme Values

Case Number Value

Unstandardized Residual Highest 1 48 .30414

2 54 .19954

Tests of Normality

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Unstandardized Residual .118 89 .004 .905 89 .000

(8)

UJI NORMALITAS (SETELAH DATA NORMAL)

Cases

Valid Missing Total

Descriptives

Unstandardized Residual Mean

- 1.6624433E-18

.00968460

Lower Bound

- 1.9252345E-2

Upper Bound _.0192523

5% Trimmed Mean _.0032771

Median .0046355

Variance _.008

Std. Deviation _.09033192

Minimum _-.37556

Maximum .19978

Range .57534

Interquartile Range .08607

Skewness -.802 .258

Kurtosis 3.065 .511

M-Estimators

Tukey's Biweightb

Hampel's

Unstandardized Residual .0031073 .0033212 .0044216 .0030918

(9)

Percentiles

Percentiles

5 10 25 50 75 90 95

-Tukey's Hinges

-Extreme Values

Case Number Value

2 17 .17439

(10)

UJI HETEROKEDASTISITAS

Variables Entered/Removedb

Model

Variables Entered

Variables

Removed Method

1 PPE_TA,

DELTAREV_TAa . Enter

a. All requested variables entered. b. Dependent Variable: ABS_1

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate

1 .122a .015 -.009 .0640649

a. Predictors: (Constant), PPE_TA, DELTAREV_TA

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression .005 2 .003 .636 .532a

Residual _.345 ₈₄ _.004

Total _.350 ₈₆

a. Predictors: (Constant), PPE_TA, DELTAREV_TA b. Dependent Variable: ABS_1

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.

B Std. Error Beta

1 (Constant) _.074 _.013 _5.841 _.000

DELTAREV_TA .002 .003 .057 .528 .599

PPE_TA -.026 .027 -.105 -.971 .334

(11)

UJI MULTIKOLINEARITAS

Coefficientsa

Model

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) _.031 _.018 _1.687 _.095

DELTAREV_TA .005 .005 .115 1.093 .278 .998 1.002

PPE_TA -.093 .039 -.251 -2.395 .019 .998 1.002

a. Dependent Variable: TAC_TA

UJI AUTOKORELASI

Model Summaryb

Model R R Square

Adjusted R Square

Std. Error of the

Estimate Durbin-Watson

1 .281a .079 .057 .0914010 2.067

(12)

PENGUJIAN PENGHITUNGAN MANAJEMEN LABA

Model

Variables Entered

Variables

Removed Method

1 PPE_TA,

DELTAREV_TAa . Enter

a. All requested variables entered. b. Dependent Variable: TAC_TA

Model Summaryb

Model R R Square

Adjusted R Square

Std. Error of the

1 .281a .079 .057 .0914010 2.067

a. Predictors: (Constant), PPE_TA, DELTAREV_TA b. Dependent Variable: TAC_TA

ANOVAb

1 Regression .060 2 .030 3.595 .032a

Residual _.702 ₈₄ _.008

Total _.762 ₈₆

a. Predictors: (Constant), PPE_TA, DELTAREV_TA b. Dependent Variable: TAC_TA

Coefficientsa

Model

t Sig.

1 (Constant) _.031 _.018 _1.687 _.095

DELTAREV_TA .005 .005 .115 1.093 .278 .998 1.002

PPE_TA -.093 .039 -.251 -2.395 .019 .998 1.002

(13)

LAMPIRAN 3

OUTPUT DATA

UJI ASUMSI KLASIK DAN

(14)

UJI ASUMSI KLASIK HIPOTESIS

UJI NORMALITAS (SEBELUM DATA NORMAL 87 DATA)

Cases

Valid Missing Total

Descriptives

Unstandardized Residual Mean .0000000 .00669414

Lower Bound

- 1.3307506E-2

Upper Bound .0133075

5% Trimmed Mean

-Std. Deviation _.06243876

Minimum _-.06840

Maximum .31439

Range .38279

Interquartile Range _.06156

Skewness 2.084 .258

Kurtosis 6.595 .511

M-Estimators

Tukey's Biweightb

Hampel's

Unstandardized Residual -.0149405 -.0219792 -.0151838 -.0222984

(15)

Percentiles

Percentiles

5 10 25 50 75 90 95

-Tukey's Hinges

-Extreme Values

Case Number Value

2 23 .14669

(16)

UJI NORMALITAS (SEBELUM DATA NORMAL 77 DATA)

Cases

Valid Missing Total

Descriptives

Lower Bound

- 9.5664117E-3

5% Trimmed Mean

-Std. Deviation .04214795

Minimum _-.05571

Maximum _.12605

Range _.18175

Skewness 1.222 .274

Kurtosis .966 .541

M-Estimators

Tukey's Biweightb

Hampel's

(17)

Percentiles

Percentiles

5 10 25 50 75 90 95

-Tukey's Hinges

-Extreme Values

Case Number Value

2 75 .10357

(18)

UJI NORMALITAS (SEBELUM DATA NORMAL 67 DATA)

Cases

Valid Missing Total

Descriptives

Lower Bound

- 7.6476492E-3

5% Trimmed Mean

Minimum _-.04429

Maximum _.09030

Range _.13459

Skewness 1.067 .293

Kurtosis .962 .578

M-Estimators

Tukey's Biweightb

Hampel's

(19)

Percentiles

Percentiles

5 10 25 50 75 90 95

-Tukey's Hinges

-Extreme Values

Case Number Value

2 67 .08358

(20)

UJI NORMALITAS (SETELAH DATA NORMAL)

Cases

Valid Missing Total

Descriptives

Lower Bound

- 6.1176996E-3

5% Trimmed Mean

Minimum _-.03959

Maximum _.07165

Range _.11124

Skewness .609 .306

Kurtosis -.006 .604

M-Estimators

Tukey's Biweightb

Hampel's

(21)

Percentiles

Percentiles

5 10 25 50 75 90 95

-Tukey's Hinges

-Extreme Values

Case Number Value

2 14 .04947

Unstandardized Residual .097 61 .200* .962 61 .057

a. Lilliefors Significance Correction

(22)

UJI HETEROKEDASTISITAS

Model

Variables Entered

Variables

Removed Method

1 KI, KDK, UDK,

FPKA, KMa . Enter

a. All requested variables entered. b. Dependent Variable: ABS_2

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate

1 .205a .042 -.045 .0135484

a. Predictors: (Constant), KI, KDK, UDK, FPKA, KM

ANOVAb

1 Regression .000 5 .000 .480 .790a

Residual _.010 ₅₅ _.000

Total _.011 ₆₀

a. Predictors: (Constant), KI, KDK, UDK, FPKA, KM b. Dependent Variable: ABS_2

Coefficientsa

Model

t Sig.

(23)

UJI MULTIKOLINEARITAS

Coefficientsa

Model

t Sig.

a. Dependent Variable: DA

UJI AUTOKORELASI

Model Summaryb

Model R R Square

Adjusted R Square

Std. Error of the

1 .720a .518 .474 .0249490 2.206

a. Predictors: (Constant), KI, KDK, UDK, FPKA, KM b. Dependent Variable: DA

STATISTIK DESKRIPTIF

Descriptive Statistics

(24)

PENGUJIAN HIPOTESIS

Model

Variables Entered

Variables

Removed Method

1 KI, KDK, UDK,

FPKA, KMa . Enter

a. All requested variables entered. b. Dependent Variable: DA

Model Summaryb

Model R R Square

Adjusted R Square

Std. Error of the

1 .720a .518 .474 .0249490 2.206

ANOVAb

1 Regression .037 5 .007 11.829 .000a

Residual _.034 ₅₅ _.001

Total _.071 ₆₀

Coefficientsa

Model

t Sig.