55
DAFTAR PUSTAKA Almilia, Luciana Spica dan Lucas Setiady. 2006. “Faktor-Faktor yang Mempengaruhi Penyelesaian Penyajian Laporan Keuangan pada Perusahaan yang Terdaftar Di BEJ”. Seminar Nasional Good Corporate Governance. Jakarta: Universitas Trisakti. Arens, Elder dan Beasley. 2008. Auditing and Assurance Services. Edisi Keduabelas. Jilid Pertama. Jakarta: Erlangga. Arens and Loebbecke. Auditing, Terjemahan : Amir Abadi Yusuf . (1996). Auditing Pendekatan Terpadu, Jakarta : Salemba Empat. Dogan, Mustafa, Ender Coskun and Orhan Celik. 2007. “Is Timing of Financial Reporting Related to Firm Performance? An Examination on Ise Listed Companies”. International Research Journal of Finance and Economics. Issue 12. EuroJournals Publishing, Inc. Ghozali, Imam. 2005. Aplikasi Analisis Multivariate dengan Program SPSS. Semarang: Badan Penerbit Universitas Diponegoro. Hilmi, Utari dan Syaiful Ali. 2008. ”Analisis Faktor-Faktor Yang Memepengaruhi Ketepatan Waktu Penyampaian Laporan Keuangan (Studi Empiris pada Perusahaan-perusahaan yang Terdaftar di BEJ)”. Simposium Nasional Akuntansi XI Ikatan Akuntan Indonesia. Jensen, M. C. dan Meckling, W. H. 1976. ”Theory of Firm: Managerial Behaviour, Agency Costs and Ownership Structure”. Journal of Financial Economics.3. Pp. 305-360. Kadir, Abdul. 2008. Faktor-Faktor yang Berpengaruh Terhadap Ketepatan Waktu Pelaporan Keuangan. Tesis Tidak Dipublikasikan. Fakultas Ekonomi Universitas Diponegoro. Kieso, Weygandt, dan Warfield. 2007. Intermediate Accounting. Edisi Keduabelas. Jilid Kedua. Jakarta: Erlangga Kieso, Weygandt, dan Warfield. 2011. Intermediate Accounting IFRS Edision. Volume Pertama. United States of America: Wilay Ukago, Kristianus. 2004. Faktor-Faktor yang Berpengaruh Terhadap Ketepatan Waktu Pelaporan Keuangan Bukti Empiris Emiten di Bursa Efek Jakarta. Tesis Tidak Dipublikasikan. Fakultas Ekonomi Universitas Diponegoro. www.bapepam.go.id
56
LAMPIRAN I Contoh Laporan Auditor Independen
57
58
LAMPIRAN II Hasil Output Descriptives Notes Output Created
19-Mar-2012 19:42:17
Comments Input
Active Dataset
DataSet0
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File Missing Value Handling
100
Definition of Missing
User defined missing values are treated as missing.
Cases Used
All non-missing data are used.
Syntax
DESCRIPTIVES VARIABLES=AGE /STATISTICS=MEAN STDDEV MIN MAX.
Resources
Processor Time
00 00:00:00.094
Elapsed Time
00 00:00:00.301
[DataSet0]
Descriptive Statistics N
Minimum
AGE
100
Valid N (listwise)
100
5.00
Maximum 113.00
Mean 40.1200
Std. Deviation 25.49164
FREQUENCIES VARIABLES=KAP /ORDER=ANALYSIS.
59
Frequencies Notes Output Created
19-Mar-2012 19:43:26
Comments Input
Active Dataset
DataSet0
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File Missing Value Handling
100
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Syntax
FREQUENCIES VARIABLES=KAP /ORDER=ANALYSIS.
Resources
Processor Time
00 00:00:00.031
Elapsed Time
00 00:00:00.020
[DataSet0] Statistics KAP N
Valid
100
Missing
0
KAP Frequency Valid
Percent
Valid Percent
Cumulative Percent
.00
36
36.0
36.0
36.0
1.00
64
64.0
64.0
100.0
Total
100
100.0
100.0
FREQUENCIES VARIABLES=OP /ORDER=ANALYSIS.
60
Notes Output Created
19-Mar-2012 19:43:45
Comments Input
Active Dataset
DataSet0
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File Missing Value Handling
100
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on all cases with valid data.
Syntax
FREQUENCIES VARIABLES=OP /ORDER=ANALYSIS.
Resources
Processor Time
00 00:00:00.000
Elapsed Time
00 00:00:00.011
[DataSet0]
Statistics OP N
Valid
100
Missing
0
OP Frequency Valid
Percent
Valid Percent
Cumulative Percent
.00
5
5.0
5.0
5.0
1.00
95
95.0
95.0
100.0
Total
100
100.0
100.0
LOGISTIC REGRESSION VARIABLES KETEPATAN_WAKTU /METHOD=FSTEP(COND) AGE KAP OP /CLASSPLOT /CASEWISE OUTLIER(2) /PRINT=GOODFIT CORR ITER(1) CI(95) /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5)
61
Logistic Regression Notes Output Created
12-Mar-2012 13:08:50
Comments Input
Active Dataset
DataSet0
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File Missing Value Handling
100
Definition of Missing
User-defined missing values are treated as missing
Syntax
LOGISTIC REGRESSION VARIABLES KETEPATAN_WAKTU /METHOD=ENTER AGE KAP OP /CLASSPLOT /PRINT=GOODFIT CORR ITER(1) CI(95) /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).
Resources
Processor Time
0:00:00.046
Elapsed Time
0:00:00.078
Case Processing Summary Unweighted Casesa Selected Cases
N Included in Analysis Missing Cases Total
Unselected Cases Total
Percent 100
100.0
0
.0
100
100.0
0
.0
100
100.0
a. If weight is in effect, see classification table for the total number of cases.
62
Dependent Variable Encoding Original Value
Internal Value
.00
0
1.00
1
Block 0: Beginning Block Iteration Historya,b,c Coefficients Iteration Step 0
-2 Log likelihood
Constant
1
52.870
1.760
2
45.943
2.453
3
45.401
2.716
4
45.394
2.751
5
45.394
2.752
a. Constant is included in the model. b. Initial -2 Log Likelihood: 45,394 c. Estimation terminated at iteration number 5 because parameter estimates changed by less than ,001. Classification Tablea,b Predicted KETEPATAN_WAKTU Observed Step 0
KETEPATAN_WAKTU
Overall Percentage
.00
1.00
Percentage Correct
.00
0
6
.0
1.00
0
94
100.0
94.0
a. Constant is included in the model. b. The cut value is ,500
63
Variables in the Equation
B
Step 0
Constant
S.E. 2.752
Wald .421
df
Sig.
42.700
1
Exp(B) .000
15.667
Variables not in the Equation
Score
Step 0
Variables
df
Sig.
AGE
.000
1
.983
KAP
2.605
1
.107
OP
27.212
1
.000
27.752
3
.000
Overall Statistics Block 1: Method = Enter Iteration Historya,b,c,d
Coefficients Iteration Step 1
-2 Log likelihood
Constant
AGE
KAP
OP
1
44.928
-.327
-.003
.038
2.291
2
34.512
-.213
-.008
.101
3.214
3
32.720
-.059
-.014
.179
3.793
4
32.574
.025
-.017
.214
4.026
5
32.572
.036
-.017
.217
4.058
6
32.572
.036
-.017
.217
4.058
a. Method: Enter b. Constant is included in the model. c. Initial -2 Log Likelihood: 45,394 d. Estimation terminated at iteration number 6 because parameter estimates changed by less than ,001.
64
Omnibus Tests of Model Coefficients
Chi-square
Step 1
df
Sig.
Step
12.822
3
.005
Block
12.822
3
.005
Model
12.822
3
.005
Model Summary Step
-2 Log likelihood
Cox & Snell R Square
32.572a
1
Nagelkerke R Square
.120
.330
a. Estimation terminated at iteration number 6 because parameter estimates changed by less than ,001. Hosmer and Lemeshow Test Step
Chi-square
1
df
Sig.
5.668
8
.684
Contingency Table for Hosmer and Lemeshow Test
KETEPATAN_WAKTU = ,00
Observed
Step 1
KETEPATAN_WAKTU = 1,00
Expected
Observed
Expected
Total
1
3
3.428
7
6.572
10
2
1
.575
10
10.425
11
3
0
.382
11
10.618
11
4
1
.307
9
9.693
10
5
0
.250
9
8.750
9
6
1
.259
9
9.741
10
7
0
.259
11
10.741
11
8
0
.224
10
9.776
10
9
0
.192
10
9.808
10
10
0
.124
8
7.876
8
65
Classification Tablea Predicted KETEPATAN_WAKTU Observed Step 1
.00
KETEPATAN_WAKTU
1.00
Percentage Correct
.00
3
3
50.0
1.00
2
92
97.9
Overall Percentage
95.0
a. The cut value is ,500 Variables in the Equation
95% C.I.for EXP(B)
B
Step 1a
S.E.
Wald
df
Sig.
Exp(B)
Lower
Upper
AGE
-.017
.019
.877
1
.349
.983
.947
1.019
KAP
.217
1.261
.030
1
.863
1.242
.105
14.720
OP
4.058
1.439
7.955
1
.005
57.866
3.449
970.767
.036
1.029
.001
1
.972
1.037
Constant
a. Variable(s) entered on step 1: AGE, KAP, OP. Correlation Matrix
Constant
Step 1
AGE
KAP
OP
Constant
1.000
-.452
.056
-.435
AGE
-.452
1.000
-.123
-.296
KAP
.056
-.123
1.000
-.540
OP
-.435
-.296
-.540
1.000
66
Step number: 1 Observed Groups and Predicted Probabilities 80 + + | | | | F | R + E | Q | U 1 E 1 N 1 C 1 Y 11
| 60 + | | | | 40 + + | | | | | | 20 +
11
+ |
111 | | 111 | | 1 1111 | Predicted ---------+---------+---------+---------+---------+---------+---------+---------+--------+---------Prob: 0 ,1 ,2 ,3 ,4 ,5 ,6
67
Regression Notes Output Created
19-Mar-2012 19:47:20
Comments Input
Active Dataset
DataSet0
Filter
<none>
Weight
<none>
Split File
<none>
N of Rows in Working Data File Missing Value Handling
100
Definition of Missing
User-defined missing values are treated as missing.
Cases Used
Statistics are based on cases with no missing values for any variable used.
Syntax
REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT KETEPATAN_WAKTU /METHOD=ENTER AGE KAP OP.
Resources
Processor Time
00 00:00:00.078
Elapsed Time
00 00:00:00.066
Memory Required
1948 bytes
Additional Memory Required for
0 bytes
Residual Plots
[DataSet0]
Variables Entered/Removedb Model 1
Variables Entered
Variables Removed
OP, AGE, KAP
Method . Enter
a. All requested variables entered. b. Dependent Variable: KETEPATAN_WAKTU
68
Model Summary Std. Error of the Model
R
R Square .527a
1
Adjusted R Square
.278
Estimate
.255
.20602
a. Predictors: (Constant), OP, AGE, KAP
ANOVAb Model 1
Sum of Squares
df
Mean Square
F
Regression
1.565
3
.522
Residual
4.075
96
.042
Total
5.640
99
Sig. .000a
12.292
a. Predictors: (Constant), OP, AGE, KAP b. Dependent Variable: KETEPATAN_WAKTU
Coefficientsa Standardized Unstandardized Coefficients Model 1
B (Constant)
Coefficients
Std. Error
Beta
.418
.095
AGE
-.001
.001
KAP
.010
OP
.573
t
Sig. 4.420
.000
-.076
-.847
.399
.046
.019
.208
.836
.099
.526
5.759
.000
a. Dependent Variable: KETEPATAN_WAKTU
