b,c b b,c,d

81 Lampiran 6 Hasil output spss Descriptive Statistics N Minimum Maximum Mean Std. Deviation PRESTISE_PEND 56 .1667 .8750 .5914 .1936 STRATA_PEND 56 2 3.1667 2.4687 .2486 UDK 56 2 10 5.27 1.814 UDD 56 2 12 5.25 1.719 LEVERAGE 56 -24.1183 14.8127 1.327 5.0796 Valid N listwise 56 Case Processing Summary Unweighted Cases a N Percent Selected Cases Included in Analysis 56 90.3 Missing Cases 6 9.7 Total 62 100.0 Unselected Cases .0 Total 62 100.0 a. If weight is in effect, see classification table for the total number of cases. Dependent Variable Encoding Original Value Internal Value Non Distress Distress 1 Block 0: Beginning Block Iteration History

a,b,c

Iteration -2 Log likelihood Coefficients Constant Step 0 1 67.047 -.857 2 67.006 -.916 3 67.006 -.916 a. Constant is included in the model. b. Initial -2 Log Likelihood: 67.006 Universitas Sumatera Utara 82 c. Estimation terminated at iteration number 3 because parameter estimates changed by less than .001. Classification Table

a,b

Observed Predicted FD Percentage Correct Non Distress Distress Step 0 FD Non Distress 40 100.0 Distress 16 .0 Overall Percentage 71.4 a. Constant is included in the model. b. The cut value is .500 Variables in the Equation B S.E. Wald df Sig. ExpB Step 0 Constant -.916 .296 9.595 1 .002 .400 Variables not in the Equation Score df Sig. Step 0 Variables PRESTISE_PEND .153 1 .695 STRATA_PEND 4.174 1 .041 UDK 3.715 1 .054 UDD .754 1 .385 Overall Statistics 10.832 4 .029 Universitas Sumatera Utara 83 Block 1: Method = Enter Iteration History

a,b,c,d

Iteration -2 Log likelihood Coefficients Constant PRESTISE _PEND STRATA_P END UDK UDD Step 1 1 56.417 2.764 -2.270 -2.053 .316 .214 2 54.635 4.953 -3.090 -3.312 .438 .307 3 54.524 5.763 -3.318 -3.760 .476 .335 4 54.524 5.834 -3.336 -3.798 .479 .337 5 54.524 5.834 -3.336 -3.798 .479 .337 a. Method: Enter b. Constant is included in the model. c. Initial -2 Log Likelihood: 67.006 d. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001. Omnibus Tests of Model Coefficients Chi-square df Sig. Step 1 Step 12.483 4 .014 Block 12.483 4 .014 Model 12.483 4 .014 Model Summary Step -2 Log likelihood Cox Snell R Square Nagelkerke R Square 1 54.524 a .200 .286 a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001. Hosmer and Lemeshow Test Step Chi-square df Sig. 1 11.422 7 .121 Universitas Sumatera Utara 84 Contingency Table for Hosmer and Lemeshow Test FD = Non Distress FD = Distress Total Observed Expected Observed Expected Step 1 1 6 5.806 .194 6 2 6 5.600 .400 6 3 3 5.339 3 .661 6 4 4 4.089 1 .911 5 5 6 5.424 1 1.576 7 6 6 4.728 1 2.272 7 7 4 3.658 2 2.342 6 8 3 3.006 3 2.994 6 9 2 2.351 5 4.649 7 Classification Table a Observed Predicted FD Percentage Correct Non Distress Distress Step 1 FD Non Distress 38 2 95.0 Distress 8 8 50.0 Overall Percentage 82.1 a. The cut value is .500 Variables in the Equation B S.E. Wald df Sig. ExpB Step 1 a PRESTISE_PEND -3.336 2.367 1.987 1 .159 .036 STRATA_PEND -3.798 1.891 4.036 1 .045 .022 UDK .479 .223 4.612 1 .032 1.615 UDD .337 .265 1.618 1 .203 1.401 Constant 5.834 4.121 2.005 1 .157 341.741 a. Variables entered on step 1: PRESTISE_PEND, STRATA_PEND, UDK, UDD. Universitas Sumatera Utara 85 Correlation Matrix Constant PRESTISE_ PEND STRATA_P END UDK UDD Step 1 Constant 1.000 .069 -.945 .001 .067 PRESTISE_PEND .069 1.000 -.088 -.534 -.404 STRATA_PEND -.945 -.088 1.000 -.133 -.252 UDK .001 -.534 -.133 1.000 .036 UDD .067 -.404 -.252 .036 1.000 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .446 a .198 .150 .408 a. Predictors: Constant, Ln_LEVPRESTISE, Ln_PRESTISE, Ln_LEVERAGE ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 2.058 3 .686 4.127 .011 b Residual 8.312 50 .166 Total 10.370 53 a. Dependent Variable: Financial Distress b. Predictors: Constant, Ln_LEVPRESTISE, Ln_PRESTISE, Ln_LEVERAGE Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant .210 .100 2.096 .041 Ln_LEVERAGE -.063 .097 -.167 -.646 .521 Ln_PRESTISE -.189 .130 -.190 -1.453 .153 Ln_LEVPREST -.393 .179 -.556 -2.194 .033 a. Dependent Variable: Financial Distress Universitas Sumatera Utara 86 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .485 a .236 .190 .398 a. Predictors: Constant, Ln_LEVSTRATA, Ln_STRATA, Ln_LEVERAGE ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 2.442 3 .814 5.134 .004 b Residual 7.928 50 .159 Total 10.370 53 a. Dependent Variable: Financial Distress b. Predictors: Constant, Ln_LEVSTRATA, Ln_STRATA, Ln_LEVERAGE Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant 1.290 .506 2.547 .014 Ln_LEVERAGE 1.075 .410 2.848 2.621 .012 Ln_STRATA -1.104 .558 -.249 -1.978 .053 Ln_LEVSTRATA -1.029 .439 -2.554 -2.346 .023 a. Dependent Variable: Financial Distress Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .291 a .085 .030 .436 a. Predictors: Constant, Ln_LEVUDK, Ln_UDK, Ln_LEVERAGE ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression .881 3 .294 1.546 .214 b Residual 9.490 50 .190 Total 10.370 53 a. Dependent Variable: Financial Distress b. Predictors: Constant, Ln_LEVUDK, Ln_UDK, Ln_LEVERAGE Universitas Sumatera Utara 87 Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant .053 .294 .182 .856 Ln_LEVERAGE -.035 .312 -.093 -.113 .911 Ln_UDK .132 .178 .104 .743 .461 Ln_LEVUDK .085 .199 .352 .428 .670 a. Dependent Variable: Financial Distress Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .280 a .078 .023 .437 a. Predictors: Constant, Ln_ LEVUDD, Ln_UDD, Ln_LEVERAGE ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression .814 3 .271 1.419 .248 b Residual 9.557 50 .191 Total 10.370 53 a. Dependent Variable: Financial Distress b. Predictors: Constant, Ln_ LEVUDD, Ln_UDD, Ln_LEVERAGE Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 Constant .414 .322 1.285 .205 Ln_LEVERAGE .144 .327 .380 .440 .662 Ln_UDD -.088 .204 -.067 -.433 .667 Ln_LEVUDD -.019 .179 -.091 -.103 .918 a. Dependent Variable: Financial Distress Universitas Sumatera Utara 88 Lampiran 7 Nilai Chi-Square Tabel Chi-square Distribution Table d.f. .995 .99 .975 .95 .9 .1 .05 .025 .01 1 0.00 0.00 0.00 0.00 0.02 2.71 3.84 5.02 6.63 2 0.01 0.02 0.05 0.10 0.21 4.61 5.99 7.38 9.21 3 0.07 0.11 0.22 0.35 0.58 6.25 7.81 9.35 11.34 4 0.21 0.30 0.48 0.71 1.06 7.78 9.49 11.14 13.28 5 0.41 0.55 0.83 1.15 1.61 9.24 11.07 12.83 15.09 6 0.68 0.87 1.24 1.64 2.20 10.64 12.59 14.45 16.81 7 0.99 1.24 1.69 2.17 2.83 12.02 14.07 16.01 18.48 8 1.34 1.65 2.18 2.73 3.49 13.36 15.51 17.53 20.09 9 1.73 2.09 2.70 3.33 4.17 14.68 16.92 19.02 21.67 10 2.16 2.56 3.25 3.94 4.87 15.99 18.31 20.48 23.21 11 2.60 3.05 3.82 4.57 5.58 17.28 19.68 21.92 24.72 12 3.07 3.57 4.40 5.23 6.30 18.55 21.03 23.34 26.22 13 3.57 4.11 5.01 5.89 7.04 19.81 22.36 24.74 27.69 14 4.07 4.66 5.63 6.57 7.79 21.06 23.68 26.12 29.14 15 4.60 5.23 6.26 7.26 8.55 22.31 25.00 27.49 30.58 16 5.14 5.81 6.91 7.96 9.31 23.54 26.30 28.85 32.00 17 5.70 6.41 7.56 8.67 10.09 24.77 27.59 30.19 33.41 18 6.26 7.01 8.23 9.39 10.86 25.99 28.87 31.53 34.81 19 6.84 7.63 8.91 10.12 11.65 27.20 30.14 32.85 36.19 20 7.43 8.26 9.59 10.85 12.44 28.41 31.41 34.17 37.57 22 8.64 9.54 10.98 12.34 14.04 30.81 33.92 36.78 40.29 24 9.89 10.86 12.40 13.85 15.66 33.20 36.42 39.36 42.98 26 11.16 12.20 13.84 15.38 17.29 35.56 38.89 41.92 45.64 28 12.46 13.56 15.31 16.93 18.94 37.92 41.34 44.46 48.28 30 13.79 14.95 16.79 18.49 20.60 40.26 43.77 46.98 50.89 32 15.13 16.36 18.29 20.07 22.27 42.58 46.19 49.48 53.49 34 16.50 17.79 19.81 21.66 23.95 44.90 48.60 51.97 56.06 38 19.29 20.69 22.88 24.88 27.34 49.51 53.38 56.90 61.16 42 22.14 23.65 26.00 28.14 30.77 54.09 58.12 61.78 66.21 46 25.04 26.66 29.16 31.44 34.22 58.64 62.83 66.62 71.20 50 27.99 29.71 32.36 34.76 37.69 63.17 67.50 71.42 76.15 55 31.73 33.57 36.40 38.96 42.06 68.80 73.31 77.38 82.29 60 35.53 37.48 40.48 43.19 46.46 74.40 79.08 83.30 88.38 65 39.38 41.44 44.60 47.45 50.88 79.97 84.82 89.18 94.42 70 43.28 45.44 48.76 51.74 55.33 85.53 90.53 95.02 100.43 75 47.21 49.48 52.94 56.05 59.79 91.06 96.22 100.84 106.39 80 51.17 53.54 57.15 60.39 64.28 96.58 101.88 106.63 112.33 85 55.17 57.63 61.39 64.75 68.78 102.08 107.52 112.39 118.24 90 59.20 61.75 65.65 69.13 73.29 107.57 113.15 118.14 124.12 95 63.25 65.90 69.92 73.52 77.82 113.04 118.75 123.86 129.97 100 67.33 70.06 74.22 77.93 82.36 118.50 124.34 129.56 135.81 Universitas Sumatera Utara 73 Daftar Pustaka Agoes, Sukrisno dan Cenik Ardana. 2009. Etika Bisnis dan Profesi, Tantangan Membangun Manusia Seutuhnya. Edisi revisi. Jakarta: Salemba Empat. Ahmad, G.N. 2013. “Analysis of Financial Distress in Indonesia Stock Exchange”.Society of Interdisciplinary Business Research , Vol 2 Nomor 2. Almilia, Luciana. 2006. “Prediksi Kondisi Financial Distress Perusahaan Go public Dengan Menggunakan Analisis Multinomial Logit”.Jurnal Ekonomi dan Bisnis.Volume XII Nomor 1. Altman, E, dan Hotchkiss, E. 2006. Corporate Financial Distress and Bankcruptcy, Third Edition . New Jersey: John Wiley Sons, Inc. Aron A. Gottesman dan Matthew R. Morey. 2006. “Does a better education make for better managers? An empirical examination of CEO educational quality and firm performance”. Lubin school of Business. Asquith, P., Gertner, R., and Scharfstein. 1991. “Anatomy of Financial Distress: An Examination of Junk- Bonds Issuers”. National Bureau of Economics Research Working Paper Series, No 3942 BANTEL, K. A., Jackson, S. E. 1989. Top Management and Innovation in Banking: Does the Composition of The Top Team Make A Difference? Strategic Management Journal 1986-1998. Bathala, C. T., Moon, K. P., Rao, R. P. 1994. “Managerial ownership, debt policy, and the impact of institutional holdings: An agency perspective ”. Financial Management, 233, 38. Beaver, W. 1966, Financial Ratios as Predictors of Failures .” Journal of Accounting Research, Vol. 4 Supplement, 71-102. DAveni, R.,A. 1990, “Top managerial prestige and organizational bankruptcy ”. Organization Science, 12, 121-142. Emirzon, Joni, 2007. Prinsip-prinsip Good Corporate Governance: Paradigma baru Dalam Praktik Bisnis Indonesia. Yogyakarta: Genta Press. Erlina, 2011. Metodologi Penelitian. Medan: USU Press. F. Primada. 2009. “Manfaat Rasio Keuangan dan Corporate Governance Untuk Memprediksi Kondisi Financial Distress pada Perusahaan Manufaktur Universitas Sumatera Utara 74 yang Terdaftar di BEI”, Skripsi, Fakultas ekonomi, Universitas Sebelas Maret. Hambrick, D dan Mason. 2003. “Upper Echelons: The organization as a Reflection of its Top Managers”. The Academy of Management Review, Volume 9, Issue 2 Apr., 1984, 193-206 . Hidayat, Muhammad Arif. 2013. “Prediksi Financial Distress Perusahaan Manufaktur di Indonesia Studi Empiris pada Perusahaan Manufaktur yang Terdaftar di Bursa Efek Indonesia Periode 2008- 2012”. Skripsi, Fakultas Ekonomika dan Bisnis, Universitas Diponegoro. Irdyana, Brian. 2010. “Analisi Rasio Keuangan CAMEL dan Corporate Governance dalam memprediksi Financial Distress pada Industri Perbankan di Indonesia”. Skripsi, Fakultas Ekonomi Universitas Sebelas Maret. Iqbal, Zahid. 2015. “Financial Distress around Introduction of Hedging in the Oil and Gas Industry”. International Journal of Business, 201. Jensen dan Meckling. 1976. “Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure”. Journal of Financial Economics, October, 1976, V. 3, No. 4, pp. 305-360. John, Kose. 2001. “Managing Financial Distress and Valuing Distressed Securities: A survey and a Research Agenda ” Stren School of Business, New York University, New York. Khaliq, Ahmad, dkk. 2014. “Identifying Financial Distress Firms: A Case Study of Malaysia’s Government Linked Companies GLC”. International Journal of Economics, Finance and Management. Kuncoro, Mudrajad. 2003. Metode Riset untuk Bisnis Ekonomi. Bagaimana meneliti dan menulis tesis?. Jakarta: Penerbit Erlangga. Mariana. 2015. “Analisis Pengaruh Rasio Arus Kas Terhadap Prediksi Kondisi Financial Distress Pada Perusahaan Sektor Industri Dasar dan Kimia yang t erdaftar di BEI”. Skripsi, Fakultas Ekonomi dan Bisnis, Universitas Sumatera Utara. Marshall, Eric. “What Determines the Performance of Graduates? Selection Versus Quality: Evidence From Top Law Schools ”. Ohlson, J.A. 1980, Financial Ratios and the Probabilistic Prediction of Bankruptcy, Journal of Accounting Research, Vol. 19, 109-131. Universitas Sumatera Utara 75 Penny Tamkin, Jim Hillage, Rebecca Willison. “Indicators of Management Capability: Developing a Framework ”. The Institute for Employment Studies. Platt dan Platt. 2006. “Understanding Differences between Financial Distress and Bankruptcy ”. Review of Applied Economics, Vol 2, No, 2, 2006 : 141-157. Platt dan Platt. “Financial Distress comparison accross 3 global region”. Journal of Risk and Financial Management. Purnanandam K., Amiyatosh. 2007. “Financial Distress and Corporate Risk Management: Theory Evidence ”. University of Michigan, Stephen M. Ross School of Business. Raza, Muhammad Wahid dan Shaheed Benazir Bhutto . 2013. “Affect of Financial Leverage on firm performance. Empirical Evidence on Karashi stock exchange ”. University of Seringal. Oppong, Seth. 2014. “Upper Echelons Theory Revisited : The Need For A Change from Casual Description to Casual Explanation ”. Sam Jonah School of Business, African University College of Communication. Soewadji, Jusuf. 2012. Pengantar Metodologi Penelitian. Jakarta: Mitra Wacana Media. Wardani, Ratna. 2006. “Mekanisme Corporate Governance dalam perusahaan yang mengalami permasalahan keuangan FINANCIALLY DISTRESSED FIRMS ” Universitas Indonesia. Simposium Nasional Akuntansi 9 Padang. Weill, Laurent. “Leverage and Corporate Performance: A Frontier Efficiency Analysis ” Université Robert Schuman, Institut d’Etudes Politiques, France. Whitaker, R. B. 1999. The early stages of financial distress. Journal of Economics and Finance, 23 2, 123-132. Universitas Sumatera Utara 33

BAB III METODOLOGI PENELITIAN

3.1 Desain Penelitian