08.60.0028 Debbie Intan Permata Sari LAMPIRAN

(1)

(2)

LAMPIRAN 1 :

DAFTAR PERUSAHAAN YANG

MELAPORKAN AMORTISASI

(3)

LAMPIRAN 2 :

DAFTAR JENIS INDUSTRI DAN

(4)

LAMPIRAN 3 :

DAFTAR PERUSAHAAN YANG

MEMILIKI

GOODWILL

_DAN

_TEPAT

(5)

LAMPIRAN 4 :

DAFTAR PERHITUNGAN

CUMULATIVE ABNORMAL RETURN

(CAR)

–

KELOMPOK DATA TEPAT

TANGGAL PUBLIKASI

(6)

LAMPIRAN 5 :

(7)

LAMPIRAN 6 :

(8)

UJI NORMALITAS

Model Regresi 1

Sebelum Data Normal

Case Processing Summary

Unstandardized Residual Mean .0000000 .04517470

95% Confidence Interval for Mean Lower Bound _-.0892114

Extreme Values

Case Number Value

Unstandardized Residual Highest 1 ₇₁ _5.80029

2 91 .91794

Tests of Normality

Kolmogorov-Smirnov(a) Shapiro-Wilk

(9)

Setelah Data Normal

Unstandardized Residual Mean _.0000000 _.00483275

95% Confidence Interval for Mean Lower Bound -.0095603

Extreme Values

Case Number Value

Unstandardize d Residual

Highest 1 62 .12942

Statistic df Sig. Statistic df Sig. Unstandardized Residual .065 132 .200(*) .978 132 .028 * This is a lower bound of the true significance.

(10)

Model Regresi 2

Sebelum Data Normal

Unstandardized Residual Mean _.0000000 _.04515219

95% Confidence Interval for Mean Lower Bound -.0891669

Extreme Values

Case Number Value

Highest 1 71 5.79273

(11)

Setelah Data Normal

Mean _.0000000 _.00493895

95% Confidence Interval for Mean

Lower Bound -.0097697 Upper Bound

.0097697

Extreme Values

Case Number Value

Highest 1 125 .15567

(12)

Model Regresi 3

Sebelum Data Normal

Mean _.0000000 _.04499499

.0888565

Extreme Values

Case Number Value

Highest 1 71 5.76048

(13)

Setelah Data Normal

Mean _.0000000 _.00446626

.0088400

Extreme Values

Case Number Value

Highest 1 91 .12344

(14)

Model Regresi 4

Sebelum Data Normal

Mean .0000000 .04483949

Lower Bound _-.0885494 Upper Bound

.0885494

Extreme Values

Case Number Value

Highest 1 ₇₁ _5.72756

(15)

Setelah Data Normal

Mean .0000000 .00599309

.0118479

Extreme Values

Case Number Value

Highest 1 ₄₁ _.19588

(16)

UJI MULTIKOLONIERITAS

Model Regresi 1

Coefficients(a)

Model

Unstandardized Coefficients

Standardized

Coefficients t Sig. Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) _-.001 _.005 _-.178 _.859

EPSBGW .000 .000 .092 1.048 .296 1.000 1.000 a Dependent Variable: CAR

Coefficient Correlations(a)

Model EPSBGW

1 Correlation s a Dependent Variable: CAR

Collinearity Diagnostics(a)

Model

Dimensio

n Eigenvalue

Condition Index

Variance Proportions (Constant) EPSBGW

1 1 _1.412 _1.000 _.29 _.29

2 .588 1.550 .71 .71

a Dependent Variable: CAR

Model Regresi 2

Coefficients(a) a Dependent Variable: CAR

Model EPSAGW

(17)

Variance Proportions (Constant) EPSAGW

1 1 _1.406 _1.000 _.30 _.30

2 .594 1.539 .70 .70

Model Regresi 3

Coefficients(a)

Model GWA EPSBGW

Model

Dimensio

n Eigenvalue

Condition Index

Variance Proportions (Constant) EPSBGW GWA

1 1 1.667 1.000 .18 .16 .15

2 .773 1.468 .01 .43 .66

3 _.560 _1.726 _.81 _.41 _.19

(18)

Model Regresi 4

Model Industry EPSBGW DummyGWA

Model Dimension Eigenvalue

Condition

Index Variance Proportions

(Constant) EPSBGW DummyGWA Industry

1 1 2.260 1.000 .07 .07 .07 .07

2 _.739 _1.748 _.20 _.37 _.22 _.11

3 .684 1.818 .07 .46 .47 .04

4 _.317 _2.671 _.66 _.10 _.24 _.78

(19)

UJI HETEROKEDASTISITAS

Model Regresi 1

Variables Entered/Removed(b)

Model

Variables Entered

Variables

Removed Method

1 _EPSBGW(a) _. _Enter

a All requested variables entered. b Dependent Variable: AbsRes

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .095(a) .009 .001 .03243

a Predictors: (Constant), EPSBGW

ANOVA(b)

a Predictors: (Constant), EPSBGW b Dependent Variable: AbsRes

Coefficients(a)

a Dependent Variable: AbsRes

Model Regresi 2

Model

Variables Entered

Variables

Removed Method

1 _EPSAGW(a) _. _Enter

Model Summary

1 _.093(a) _.009 _.001 _.03359

(20)

ANOVA(b)

a Predictors: (Constant), EPSAGW b Dependent Variable: AbsRes

Coefficients(a)

Model Regresi 3

Model Variables Entered

Variables

Removed Method 1

GWA, EPSBGW(a) . Enter

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 .096(a) .009 -.007 .02872 a Predictors: (Constant), GWA, EPSBGW

ANOVA(b)

Model

Sum of

Squares df Mean Square F Sig. 1 Regressio

n .001 2 .000 .566 .569(a)

Residual .101 122 .001

Total _.102 ₁₂₄

(21)

Coefficients(a)

1 (Constant

) .042 .003 14.214 .000

EPSBGW .000 .000 -.096 -1.064 .290

GWA _.000 _.000 _.012 _.132 _.895

Model Regresi 4

Model Variables Entered Variables Removed Method 1

Industry, EPSBGW, DummyGWA(a) . Enter a All requested variables entered.

b Dependent Variable: AbsRes

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 .201(a) .040 .019 .04639697 a Predictors: (Constant), Industry, EPSBGW, DummyGWA

ANOVA(b)

Model

Sum of

n .012 3 .004 1.934 .127(a)

Residual .297 138 .002

Total _.310 ₁₄₁

a Predictors: (Constant), Industry, EPSBGW, DummyGWA b Dependent Variable: AbsRes

(22)

UJI AUTOKORELASI

Model Regresi 1

Model Summary(b)

Model R R Square

Adjusted R Square

Std. Error of

the Estimate Durbin-Watson

1 .092(a) .008 .001 .0557372 2.110

a Predictors: (Constant), EPSBGW b Dependent Variable: CAR

Model Regresi 2

Model R R Square

Adjusted R Square

Std. Error of

1 _.088(a) _.008 _.000 _.0571757 _2.079

a Predictors: (Constant), EPSAGW b Dependent Variable: CAR

Model Regresi 3

Model R R Square

Adjusted R Square

Std. Error of

1 _.131(a) _.017 _.001 _.0503419 _2.015

a Predictors: (Constant), GWA, EPSBGW b Dependent Variable: CAR

Model Regresi 4

Model R R Square

Adjusted R Square

Std. Error of

the Estimate Durbin-Watson 1 .121(a) .015 -.007 .0721880 1.929 a Predictors: (Constant), Industry, EPSBGW, DummyGWA

(23)

LAMPIRAN 7 :

STATISTIK DESKRIPTIF -

(24)

Model Regresi 1

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

CAR 132 -.1102 .1296 .001352 .0557582

EPSBGW ₁₃₂ _-1309.52 _1616.65 _164.1537 _364.40359

Valid N (listwise) 132

Model Regresi 2

CAR 133 -.1102 .1579 .002529 .0571812

EPSAGW ₁₃₃ _-1312.00 _1610.00 _160.3347 _361.95426

Model Regresi 3

CAR 125 -.1102 .1296 .001658 .0503668

EPSBGW ₁₂₅ _-1309.52 _1616.65 _164.9626 _373.54307 GWA

125 774715.00 36023300_0000.00 21272301_166.2080 55682896545.₀₅₀₆₀

Model Regresi 4

CAR 142 -.2090 .2058 .003280 .0719464

(25)

LAMPIRAN 8 :

MODEL REGRESI 1 - PENGUJIAN

UTAMA (KELOMPOK DATA TEPAT

TANGGAL PUBLIKASI)

(26)

Correlations

Model

Variables Entered

Variables

Removed Method 1 EPSBGW(a

) . Enter

a All requested variables entered. b Dependent Variable: CAR

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 _.092(a) _.008 _.001 _.0557372 a Predictors: (Constant), EPSBGW

ANOVA(b)

Model

Sum of

n .003 1 .003 1.099 .296(a)

Residual .404 130 .003

Total _.407 ₁₃₁

Coefficients(a)

1 (Constant

) -.001 .005 -.178 .859

EPSBGW _.000 _.000 _.092 _1.048 _.296

(27)

LAMPIRAN 9 :

(28)

Correlations

Model

Variables Entered

Variables

Removed Method 1 EPSAGW(a

) . Enter

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 .088(a) .008 .000 .0571757 a Predictors: (Constant), EPSAGW

ANOVA(b)

Model

Sum of

n .003 1 .003 1.025 .313(a)

Residual .428 131 .003

Total _.432 ₁₃₂

Coefficients(a)

1 (Constant

) .000 .005 .055 .956

EPSAGW _.000 _.000 _.088 _1.012 _.313

(29)

LAMPIRAN 10 :

(30)

Correlations

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 _.131(a) _.017 _.001 _.0503419 a Predictors: (Constant), GWA, EPSBGW

ANOVA(b)

Coefficients(a)

1 (Constant

) .000 .005 .081 .935

EPSBGW .000 .000 .117 1.298 .197

GWA _.000 _.000 _-.071 _-.787 _.433

(31)

LAMPIRAN 11 :

(32)

Correlations

Model

Variables Entered

Variables

Removed Method 1 _Industry,

EPSBGW, DummyGW

A(a)

. Enter a All requested variables entered.

b Dependent Variable: CAR

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 .121(a) .015 -.007 .0721880 a Predictors: (Constant), Industry, EPSBGW, DummyGWA

ANOVA(b)

a Predictors: (Constant), Industry, EPSBGW, DummyGWA b Dependent Variable: CAR

(33)

LAMPIRAN 12 :

DAFTAR PERHITUNGAN

CUMULATIVE ABNORMAL RETURN

(CAR)

–

KELOMPOK DATA

GABUNGAN

(34)

LAMPIRAN 13 :

DAFTAR PERHITUNGAN GWA,

EPSAGW, EPSBGW

–

KELOMPOK

DATA GABUNGAN

(35)

LAMPIRAN 14 :

(36)

UJI NORMALITAS

Model Regresi 1

Sebelum Data Normal

Mean .0000000 .02686733

.0528523

Extreme Values

Case Number Value

Highest 1 ₁₁₆ _7.34666

(37)

Setelah Data Normal

Mean _.0000000 _.00108056

.0021822

Extreme Values

Case Number Value

Highest 1 8 .01042

(38)

Model Regresi 2

Sebelum Data Normal

Mean _.0000000 _.02684243

.0528033

Extreme Values

Case Number Value

Highest 1 116 7.32860

(39)

Setelah Data Normal

Mean _.0000000 _.00111235

.0022404

Extreme Values

Case Number Value

Highest 1 37 .01225

(40)

Model Regresi 3

Sebelum Data Normal

Mean .0000000 .02683314

.0527850

Extreme Values

Case Number Value

Highest 1 ₁₁₆ _7.33560

(41)

Setelah Data Normal

Mean _.0000000 _.00108063

.0021716

Extreme Values

Case Number Value

Highest 1 30 .01296

(42)

Model Regresi 4

Sebelum Data Normal

Mean _.0000000 _.02682313

.0527653

Extreme Values

Case Number Value

Highest 1 116 7.32820

(43)

Setelah Data Normal

Mean _.0000000 _.00102305

.0020646

Extreme Values

Case Number Value

Highest 1 9 .01085

(44)

UJI MULTIKOLONIERITAS

Model Regresi 1

Model EPSBGW

Model

Dimensio

n Eigenvalue

Condition Index

Variance Proportions (Constant) EPSBGW

1 1 _1.462 _1.000 _.27 _.27

2 .538 1.648 .73 .73

Model Regresi 2

Model EPSAGW

(45)

Model Dimension Eigenvalue Condition Index Variance Proportions

(Constant) EPSAGW

1 1 _1.354 _1.000 _.32 _.32

2 .646 1.448 .68 .68

Model Regresi 3

Model GWA EPSBGW

Condition

(Constant) EPSBGW GWA

1 1 _1.751 _1.000 _.16 _.15 _.15

2 .663 1.624 .01 .52 .69

3 .586 1.728 .84 .33 .17

(46)

Model Regresi 4

Model Industry EPSBGW DummyGWA

Condition

(Constant) EPSBGW DummyGWA Industry

1 1 _2.445 _1.000 _.06 _.06 _.06 _.06

2 .724 1.838 .50 .05 .30 .02

3 _.489 _2.235 _.02 _.71 _.11 _.35

4 .342 2.673 .42 .18 .54 .58

(47)

UJI HETEROKEDASTISITAS

Model Regresi 1

Model Variables Entered Variables Removed Method

1 EPSBGW(a) . Enter

Model Summary

1 .021(a) .000 -.025 .00352

a Predictors: (Constant), EPSBGW

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression .000 1 .000 .018 .895(a)

Residual _.000 ₄₀ _.000

Total .000 41

a Predictors: (Constant), EPSBGW b Dependent Variable: AbsRes

Coefficients(a)

Model Regresi 2

Model Variables Entered Variables Removed Method

1 _EPSAGW(a) _. _Enter

Model Summary

1 _.049(a) _.002 _-.020 _.00384

(48)

ANOVA(b)

1 Regression .000 1 .000 .107 .745(a)

Residual _.001 ₄₄ _.000

Total .001 45

a Predictors: (Constant), EPSAGW b Dependent Variable: AbsRes

Coefficients(a)

Model Regresi 3

Model Summary

1 _.236(a) _.055 _.015 _.00377

a Predictors: (Constant), GWA, EPSBGW

ANOVA(b)

1 Regression _.000 ₂ _.000 _1.380 _.261(a)

Residual .001 47 .000

Total _.001 ₄₉

(49)

Coefficients(a)

Model Regresi 4

Industry, EPSBGW,

DummyGWA(a) . Enter

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate

1 .279(a) .078 .007 .00359

a Predictors: (Constant), Industry, EPSBGW, DummyGWA

ANOVA(b)

a Predictors: (Constant), Industry, EPSBGW, DummyGWA b Dependent Variable: AbsRes

Coefficients(a)

(50)

UJI AUTOKORELASI

Model Regresi 1

Model R R Square

Adjusted R Square

Std. Error of

1 _.336(a) _.113 _.091 _.0070898 _1.901

Model Regresi 2

Model R R Square

Adjusted R Square

Std. Error of

1 .162(a) .026 .004 .0076296 1.999

Model Regresi 3

Model R R Square

Adjusted R Square

Std. Error of

1 _.492(a) _.242 _.209 _.0078021 _2.346

Model Regresi 4

Model R R Square

Adjusted R Square

Std. Error of

1 .471(a) .221 .162 .0069618 1.877

(51)

LAMPIRAN 15 :

STATISTIK DESKRIPTIF -

PENGUJIAN TAMBAHAN

(52)

Model Regresi 1

CAR ₄₂ _-.0152 _.0100 _-.003257 _.0074356

EPSBGW 42 -523.98 1848.11 213.7300 415.68802

Valid N (listwise) ₄₂

Model Regresi 2

CAR 46 -.0159 .0100 -.003052 .0076454

EPSAGW ₄₆ _-1095.50 _1348.00 _136.4274 _364.04568

Model Regresi 3

CAR 50 -.0160 .0254 -.003082 .0087750

EPSBGW ₅₀ _-1095.10 _2276.76 _230.2814 _531.74471

GWA ₅₀ _972709.00 28427005

6600.00

Model Regresi 4

(53)

LAMPIRAN 16 :

MODEL REGRESI 1 - PENGUJIAN

TAMBAHAN (KELOMPOK

GABUNGAN)

(54)

Correlations

Model

Variables Entered

Variables

Removed Method 1 EPSBGW(a

) . Enter

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 _.336(a) _.113 _.091 _.0070898 a Predictors: (Constant), EPSBGW

ANOVA(b)

Model

Sum of

n .000 1 .000 5.097 .030(a)

Residual _.002 ₄₀ _.000

Total .002 41

Coefficients(a)

1 (Constant

) -.005 .001 -3.683 .001

EPSBGW .000 .000 .336 2.258 .030

(55)

LAMPIRAN 17 :

(56)

Correlations

Model

Variables Entered

Variables

Removed Method 1 EPSAGW(a

) . Enter

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 _.162(a) _.026 _.004 _.0076296 a Predictors: (Constant), EPSAGW

ANOVA(b)

Model

Sum of

n .000 1 .000 1.187 .282(a)

Residual _.003 ₄₄ _.000

Total .003 45

Coefficients(a)

1 (Constant

) -.004 .001 -2.923 .005

EPSAGW .000 .000 .162 1.090 .282

(57)

LAMPIRAN 18 :

(58)

Correlations

Model

Variables Entered

Variables

Removed Method

1 GWA,

EPSBGW(a )

. Enter a All requested variables entered.

b Dependent Variable: CAR

Model Summary

Model R R Square

Adjusted R Square

Std. Error of the Estimate 1 .492(a) .242 .209 .0078021 a Predictors: (Constant), GWA, EPSBGW

ANOVA(b)

Model

Sum of

n .001 2 .000 7.491 .001(a)

Residual _.003 ₄₇ _.000

Total .004 49

Coefficients(a)

1 (Constant

) -.004 .001 -3.114 .003

EPSBGW .000 .000 .475 3.653 .001

GWA _.000 _.000 _-.265 _-2.039 _.047

(59)

LAMPIRAN 19 :

(60)

Correlations

Industry, EPSBGW,

DummyGWA(a) . Enter

Model Summary

1 _.471(a) _.221 _.162 _.0069618

a Predictors: (Constant), Industry, EPSBGW, DummyGWA

ANOVA(b)

1 Regression .001 3 .000 3.699 .020(a)

Residual .002 39 .000

Total .002 42

a Predictors: (Constant), Industry, EPSBGW, DummyGWA b Dependent Variable: CAR

Coefficients(a)