DAFTAR PUSTAKA. Arens, Elder dan Beasley Auditing and Assurance Services. Edisi Keduabelas. Jilid Pertama. Jakarta: Erlangga.

Transkripsi

1 55 DAFTAR PUSTAKA Almilia, Luciana Spica dan Lucas Setiady 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 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 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 Aplikasi Analisis Multivariate dengan Program SPSS. Semarang: Badan Penerbit Universitas Diponegoro. Hilmi, Utari dan Syaiful Ali 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 Theory of Firm: Managerial Behaviour, Agency Costs and Ownership Structure. Journal of Financial Economics.3. Pp Kadir, Abdul Faktor-Faktor yang Berpengaruh Terhadap Ketepatan Waktu Pelaporan Keuangan. Tesis Tidak Dipublikasikan. Fakultas Ekonomi Universitas Diponegoro. Kieso, Weygandt, dan Warfield Intermediate Accounting. Edisi Keduabelas. Jilid Kedua. Jakarta: Erlangga Kieso, Weygandt, dan Warfield Intermediate Accounting IFRS Edision. Volume Pertama. United States of America: Wilay Ukago, Kristianus Faktor-Faktor yang Berpengaruh Terhadap Ketepatan Waktu Pelaporan Keuangan Bukti Empiris Emiten di Bursa Efek Jakarta. Tesis Tidak Dipublikasikan. Fakultas Ekonomi Universitas Diponegoro.

2 56 LAMPIRAN I Contoh Laporan Auditor Independen

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4 58 LAMPIRAN II Hasil Output Descriptives Notes Output Created 19-Mar :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: Elapsed Time 00 00:00: [DataSet0] Descriptive Statistics N Minimum Maximum Mean Std. Deviation AGE Valid N (listwise) 100 FREQUENCIES VARIABLES=KAP /ORDER=ANALYSIS.

5 59 Frequencies Notes Output Created 19-Mar :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: Elapsed Time 00 00:00: [DataSet0] Statistics KAP N Valid 100 Missing 0 KAP Frequency Percent Valid Percent Cumulative Percent Valid Total FREQUENCIES VARIABLES=OP /ORDER=ANALYSIS.

6 60 Notes Output Created 19-Mar :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: Elapsed Time 00 00:00: [DataSet0] Statistics OP N Valid 100 Missing 0 OP Frequency Percent Valid Percent Cumulative Percent Valid Total 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)

7 61 Logistic Regression Notes Output Created 12-Mar :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: Elapsed Time 0:00: Case Processing Summary Unweighted Cases a N Percent Selected Cases Included in Analysis Missing Cases 0.0 Total Unselected Cases 0.0 Total a. If weight is in effect, see classification table for the total number of cases.

8 62 Dependent Variable Encoding Original Value Internal Value Block 0: Beginning Block Iteration History a,b,c Coefficients Iteration -2 Log likelihood Constant Step 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 Percentage Correct Step 0 KETEPATAN_WAKTU Overall Percentage 94.0 a. Constant is included in the model. b. The cut value is,500

9 63 Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 0 Constant Variables not in the Equation Score df Sig. Step 0 Variables AGE KAP OP Overall Statistics Block 1: Method = Enter Iteration History a,b,c,d Coefficients Iteration -2 Log likelihood Constant AGE KAP OP Step 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.

10 64 Omnibus Tests of Model Coefficients Chi-square df Sig. Step 1 Step Block Model Model Summary Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square a a. Estimation terminated at iteration number 6 because parameter estimates changed by less than,001. Hosmer and Lemeshow Test Step Chi-square df Sig Contingency Table for Hosmer and Lemeshow Test KETEPATAN_WAKTU =,00 KETEPATAN_WAKTU = 1,00 Observed Expected Observed Expected Total Step

11 65 Classification Table a Predicted KETEPATAN_WAKTU Observed Percentage Correct Step 1 KETEPATAN_WAKTU 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 KAP OP Constant a. Variable(s) entered on step 1: AGE, KAP, OP. Correlation Matrix Constant AGE KAP OP Step 1 Constant AGE KAP OP

12 Step number: 1 Observed Groups and Predicted Probabilities F R E Q U 1 E N 1 C 1 Y Predicted Prob: 0,1,2,3,4,5,6

13 67 Regression Notes Output Created 19-Mar :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: Elapsed Time 00 00:00: 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

14 68 Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate a a. Predictors: (Constant), OP, AGE, KAP ANOVA b Model Sum of Squares df Mean Square F Sig. 1 Regression a Residual Total 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) AGE KAP OP a. Dependent Variable: KETEPATAN_WAKTU