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
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58 LAMPIRAN II Hasil Output Descriptives Notes Output Created 19-Mar-2012 19:42:17 Comments Input Active Dataset DataSet0 Filter Weight Split File N of Rows in Working Data File 100 Missing Value Handling 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 Maximum Mean Std. Deviation AGE 100 5.00 113.00 40.1200 25.49164 Valid N (listwise) 100 FREQUENCIES VARIABLES=KAP /ORDER=ANALYSIS.
59 Frequencies Notes Output Created 19-Mar-2012 19:43:26 Comments Input Active Dataset DataSet0 Filter Weight Split File N of Rows in Working Data File 100 Missing Value Handling 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 Percent Valid Percent Cumulative Percent Valid.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 Weight Split File N of Rows in Working Data File 100 Missing Value Handling 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 Percent Valid Percent Cumulative Percent Valid.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 Weight Split File N of Rows in Working Data File 100 Missing Value Handling 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 Cases a N Percent Selected Cases Included in Analysis 100 100.0 Missing Cases 0.0 Total 100 100.0 Unselected Cases 0.0 Total 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 History a,b,c Coefficients Iteration -2 Log likelihood Constant Step 0 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 Table a,b Predicted KETEPATAN_WAKTU Observed.00 1.00 Percentage Correct Step 0 KETEPATAN_WAKTU.00 0 6.0 1.00 0 94 100.0 Overall Percentage 94.0 a. Constant is included in the model. b. The cut value is,500
63 Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 0 Constant 2.752.421 42.700 1.000 15.667 Variables not in the Equation Score df Sig. Step 0 Variables AGE.000 1.983 KAP 2.605 1.107 OP 27.212 1.000 Overall Statistics 27.752 3.000 Block 1: Method = Enter Iteration History a,b,c,d Coefficients Iteration -2 Log likelihood Constant AGE KAP OP Step 1 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 df Sig. Step 1 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 Nagelkerke R Square 1 32.572 a.120.330 a. Estimation terminated at iteration number 6 because parameter estimates changed by less than,001. Hosmer and Lemeshow Test Step Chi-square df Sig. 1 5.668 8.684 Contingency Table for Hosmer and Lemeshow Test KETEPATAN_WAKTU =,00 KETEPATAN_WAKTU = 1,00 Observed Expected Observed Expected Total Step 1 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 Table a Predicted KETEPATAN_WAKTU Observed.00 1.00 Percentage Correct Step 1 KETEPATAN_WAKTU.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 S.E. Wald df Sig. Exp(B) Lower Upper Step 1 a 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 Constant.036 1.029.001 1.972 1.037 a. Variable(s) entered on step 1: AGE, KAP, OP. Correlation Matrix Constant AGE KAP OP Step 1 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 + 80 + Step number: 1 Observed Groups and Predicted Probabilities F R 60 + + E Q U 1 E 40 + 1 + N 1 C 1 Y 11 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 Weight Split File N of Rows in Working Data File 100 Missing Value Handling 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 Additional Memory Required for 1948 bytes 0 bytes Residual Plots [DataSet0] Variables Entered/Removed b Model Variables Entered Variables Removed Method 1 OP, AGE, KAP. Enter a. All requested variables entered. b. Dependent Variable: KETEPATAN_WAKTU
68 Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate 1.527 a.278.255.20602 a. Predictors: (Constant), OP, AGE, KAP ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression 1.565 3.522 12.292.000 a Residual 4.075 96.042 Total 5.640 99 a. Predictors: (Constant), OP, AGE, KAP b. Dependent Variable: KETEPATAN_WAKTU Coefficients a Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant).418.095 4.420.000 AGE -.001.001 -.076 -.847.399 KAP.010.046.019.208.836 OP.573.099.526 5.759.000 a. Dependent Variable: KETEPATAN_WAKTU