Lampiran 1. Data Perusahaan

Similar documents
Lampiran IV. Hasil Output SPSS Versi 16.0 untuk Analisis Deskriptif

DATA SAMPEL TAHUN 2006

HASIL OUTPUT SPSS. Reliability Scale: ALL VARIABLES

LAMPIRAN I Data Perusahaan Sampel kode DPS EPS Ekuitas akpi ,97 51,04 40,

LAMPIRAN A. Tabulasi Data Perusahaan Sample

Lampiran 1. Daftar Sampel Perusahaan

CHAPTER V CONCLUSION, SUGGESTION AND LIMITATION. 1. Independent commissioner boards proportion does not negatively affect

. Enter. Model Summary b. Std. Error. of the. Estimate. Change. a. Predictors: (Constant), Emphaty, reliability, Assurance, responsive, Tangible

Rata-Rata Nilai Debt to Equity Ratio (DER) Perusahaan Otomotif yang 0, ,97 0, ,44 1,9 1,6 1,4 1,7 1,65

Perusahaan Consumer Goods yang Terdaftar di BEI ( ) Nama Perusahaan Perusahaan 1

Daftar Nama Perusahaan Sampel Tahun 2010

LAMPIRAN DAFTAR SAMPEL PENELITIAN. Kriteria No. Nama Perusahaan. Sampel Emiten

Universitas Sumatera Utara

LAMPIRAN 1 : DAFTAR PERUSAHAAN SAMPEL PERIODE

LAMPIRAN 1. Lampiran Nama dan Kondisi Perusahaan Textile No Kode Nama Perusahaan Hasil z-score FD Non-FD

UJI VALIDITAS DAN RELIABILIAS VARIABEL KOMPENSASI

TRY OUT 30 Responden Variabel Kompetensi/ x1

LAMPIRAN. Lampiran 1 Data Sampel Penelitian

TRY OUT 25 Responden Variabel Kepuasan / x1

Lampiran i Jadwal Penelitian

Industry Classification/Stock Name

Daftar Sampel Perusahaan

Lampiran 1. Daftar Perusahaan Sampel. No Kode Nama Perusahaan

Daftar Sampel Perusahaan Pertambangan. 4 BORN Borneo Lumbung Energy & Metal, Tbk

Lampiran 1 DAFTAR PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN (Menyajikan Laporan Keuangan Secara Berturut-turut)

Daftar Perusahaan Real Estate dan Property

LAMPIRAN. Daftar Perusahaan Manufaktur yang menjadi sampel. 1 AMFG PT.Asahimas Flat Glass Tbk 1. 2 INDF PT. Indofood Skses Makmur Tbk 2

LAMPIRAN. Lampiran 1. Data deviden untuk menghitung economic performance tahun

Daftar Nama Perusaahan. yang ada di Industri Consumer Goods periode

Data Nama Perusahaan Perbankan Yang Terdaftar Di BEI.

DATA PENELITIAN 1. CAR CAR (%)

Lampiran 1: Nama Perusahaan yang menjadi Sampel Penelitian

fruitfly fecundity example summary Tuesday, July 17, :13:19 PM 1

Lampiran 1. Sampel Penelitian No. Kode Nama Perusahaan 1 AISA Tiga Pilar Sejahtera Food Tbk 2 AKPI Argha Karya Prima Industry Tbk 3 ALKA Alaska

LAMPIRAN. Lampiran I. Daftar Populasi Perusahaan Properti dan Real Estate di Bursa Efek Indonesia No Kode. Kriteria Nama Perusahaan Emiten 1 2 3

Lampiran 1 Tabel 3.1 Sampel No. Kode Nama Perusahaan Sumber : didownload tanggal 13 November 2016 (data diolah)

Lampiran 1 Daftar Perusahaan Sampel 2012

Lampiran 1. Proses Pemilihan Sampel. Universitas Sumatera Utara

a. Uji kenormalan data model sebaran suhu pada band 7 citra tahun 2001 b. Uji kenormalan data model sebaran suhu pada band 4 citra tahun 2006

LAMPIRAN I FORMULIR SURVEI

Lampiran 1. Uji Validitas dan Reliability Variabel Kualitas Pelayanan

Lampiran 1. Tabel Sampel Penelitian

LAMPIRAN 1 Perusahaan Sampel Penelitian Tahun

: ( .

Daftar Perusahaan Sektor Property and Realestate yang terdaftar di BEI

Team project 2017 Dony Pratidana S. Hum Bima Agus Setyawan S. IIP

APPENDIX A. A.1 Sample of Indian MFIs

DAFTAR SAMPEL PERUSAHAAN

EXST7034 Multiple Regression Geaghan Chapter 11 Bootstrapping (Toluca example) Page 1

Guatemalan cholesterol example summary

Lampiran 1. Daftar perusahaan sampel

MODUL PELATIHAN SEM ANANDA SABIL HUSSEIN, PHD

Lampiran 1. Sampel Nama Perusahaan No Kode Perusahaan

populasi 37 ipo dan relisting 6 laporan keuangan tidak lengkap 1 laba dan modal negatif 8 lengkap 22 sampel 2011, 2012, 2013, 2014,

LAMPIRAN 1. Tabel 1. Data Indeks Harga Saham PT. ANTAM, tbk Periode 20 Januari Februari 2012

The PRINCOMP Procedure

Regression Models Course Project, 2016

Lampiran 1. Kriteria Pemilihan Sampel

Drilling Example: Diagnostic Plots

Stat 301 Lecture 30. Model Selection. Explanatory Variables. A Good Model. Response: Highway MPG Explanatory: 13 explanatory variables

Getting Started with Correlated Component Regression (CCR) in XLSTAT-CCR

Stat 401 B Lecture 31

FINANCIAL PERFORMANCE OF TWO WHEELER INDUSTRY IN INDIA

Review of Upstate Load Forecast Uncertainty Model

EMPIRICAL ANALYSIS ON ROAD TRAFFIC CRASHES IN ANAMBRA STATE, NIGERIA: ACCIDENT PREDICTION MODELING USING REGRESSION APPROACH

5. CONSTRUCTION OF THE WEIGHT-FOR-LENGTH AND WEIGHT-FOR- HEIGHT STANDARDS

Modeling Ignition Delay in a Diesel Engine

Sharif University of Technology. Graduate School of Management and Economics. Econometrics I. Fall Seyed Mahdi Barakchian

Important Formulas. Discrete Probability Distributions. Probability and Counting Rules. The Normal Distribution. Confidence Intervals and Sample Size

DAFTAR LAMPIRAN. Daftar Perusahaan yang dijadikan sampel

Appendix B STATISTICAL TABLES OVERVIEW

Lampiran 1 Item pengungkapan intellectual capital pada laporan tahunan

Universitas Sumatera Utara

Lampiran 1. Penjualan PT Honda Mandiri Bogor

MOTORCYCLE ACCIDENT MODEL ON THE ROAD SECTION OF HIGHLANDS REGION BY USING GENELARIZED LINEAR MODEL

Motor Trend Yvette Winton September 1, 2016

Motor Trend MPG Analysis

Data Hasil Olahan Populasi

Team project 2017 Dony Pratidana S. Hum Bima Agus Setyawan S. IIP

Level of service model for exclusive motorcycle lane

tool<-read.csv(file="d:/chilo/regression 7/tool.csv", header=t) tool

Cluster Analysis. Presented by: Lauren Franklin and Maria Bakarman COM 631. April 2017

Professor Dr. Gholamreza Nakhaeizadeh. Professor Dr. Gholamreza Nakhaeizadeh

LAMPIRAN 1 Daftar Perusahaan Consumer Goods yang Terdaftar di BEI ( )

female male help("predict") yhat age

Preface... xi. A Word to the Practitioner... xi The Organization of the Book... xi Required Software... xii Accessing the Supplementary Content...

Stat 301 Lecture 26. Model Selection. Indicator Variables. Explanatory Variables

LAMPIRAN UJI VALIDITAS

Technical Papers supporting SAP 2009

Relating your PIRA and PUMA test marks to the national standard

Relating your PIRA and PUMA test marks to the national standard

Análisis de la varianza (II)

TABLE 4.1 POPULATION OF 100 VALUES 2

Stat 401 B Lecture 27

KUESIONER PENELITIAN BAGIAN 1

FINAL REPORT AP STATISTICS CLASS DIESEL TRUCK COUNT PROJECT

The Coefficient of Determination

The Session.. Rosaria Silipo Phil Winters KNIME KNIME.com AG. All Right Reserved.

Antonio Olmos Priyalatha Govindasamy Research Methods & Statistics University of Denver

TRINITY COLLEGE DUBLIN THE UNIVERSITY OF DUBLIN. Faculty of Engineering, Mathematics and Science. School of Computer Science and Statistics

Transcription:

Lampiran. Data Perusahaan NO PERUSH MV EARN DIV CFO LB.USAHA TOT.ASS ACAP 3 9 8 5 369 9678 376 ADES 75-35 - 6 3559-5977 7358 3 AQUA 5 368 65 335 797 678 53597 BATA 88 5 9 863 958 93 5 BKSL 5.3 -. 9-9 5 6 BRPT 75-78 -.3-6693 -638 65 7 CMPP 39 6 7 95 578 67 8 CTRS 6-66 5778 967 3375 9 DNKS 75 66 5 563 7373 5685 DYNA 75 3 5 89 7659 797 8699 ELTY -5-63 38-357 7638 GGRM 9 85 3 533 55 3389977 5573 3 GJTL 65-39 - 89 66 53 HDTX 9-77 - 95 6 7373 335 5 HMSP 5 8 5 965 6588 975 6 IKAI - - 8 385-98 93679 7 IMAS 7-5 - 67-5 35985 5755 8 INDF 5 8 5 7 956 36 979 9 INTA 55 88 8 65 676 5536 7355 INTD - 569 39-8 5765 INTP 9-9 - 77 683 6767 939 KLBF 5 8-85 6897 3363 87736 3 MERK 75 58 8 5795 3889 77 67 SMCB 3 66 -.75 37-56796 5976 5 SMSM 775 55 9 5 8 789 567 6 UNVR 8 6 35 89 5 788 685 7 NIPS 85-6 - 88 7379 8 9 8 MDRN 75 86-953 53733 7538 95865 9 DVLA 5-3 - 73 39387 685 38 3 LTLS 35 5 6 5 37 778 768 3 MIRA 9 7-3.6 9593 99 938 3 MYOR 55 56-83 6393 696 399 33 SMDR 37 5 5 679 985 8 3365 3 SMGR 3 53 3 55 88 987 876375 35 SMRA 55 5 7 5798 5 7 36 STTP 35 7-8 676 65 6 37 TSPC 59 7 5 85 338 33979 66395 38 TURI 33 57 6-7 9735 37 39 ZBRA 7-33 736 8 789

NO PERUSH MV EARN DIV CFO LB.USAHA TOT.ASS ACAP 65 8 8 357 876 3863 ADES 55 97-3 3-8633 697 3 AQUA 38 53 86 769 6796 88 5579 BATA 35 37 5 7 56 7786 8 5 BKSL 85-6.3-87 53-37 89 6 BRPT 5 73-3 695-33 66988 7 CMPP 35 5 8 3 3 6 3 8 CTRS 9-785 76866 797 8959 9 DNKS 5 5755 355 963 6699 DYNA 6 6 38 659 8785 56788 ELTY 7-67 8-7 77 GGRM 7 85 3 5856 3553 38 3 GJTL 5-76 559 35 HDTX 9-5 8695-7 353 5 HMSP 95 37 5 3 8657 7795 9877 6 IKAI 8 76-39 -58 888 7 IMAS 75 97-6 -593976 7763 3687 8 INDF 6 9 8 96-578 8836 5556 9 INTA 35 9-73 69 67556 INTD 5-63 - 5 878-853 77 INTP 85 83-9 5766 999 685 KLBF 3 33-6 3998 57 5538 3 MERK 95 67 678 886 55 7336 SMCB 5 78-37 365-78 77379 5 SMSM 5 5 578 63 85 58367 6 UNVR 8 8 5 98 98 3588 39853 7 NIPS 9 399-993 66 588 8 MDRN 5 6-86 5-57 79 9 DVLA 675 3-5 699 7563 39 3 LTLS 5 63 5 57-683 938 985 3 MIRA 55-69 676 89 3 MYOR 365-98 6 5799 33375 33 SMDR 5 5 5 583 36975 5858 835 3 SMGR 79 53 7 56 8355 8579 693938 35 SMRA 5 5 5 93 965 996 36 STTP 5 3-5 6 393 75 37 TSPC 575 73 3 337 398 3893 86536 38 TURI 6 53-3 85 33 66 39 ZBRA 6 3-5 83 39 8

3 NO PERUSH MV EARN DIV CFO LB.USAHA TOT.ASS ACAP 75 7.5 53 6879 555 795 ADES 6 87 953-93 3 AQUA 53 85 8 5 587 8 533 BATA 75 76 6 9 559 577 363 5 BKSL 5.58-89 -59 7 9699 6 BRPT 35 6 -. -6556-876 337768 7 CMPP 35 5-33 397 33 396 8 CTRS 975 59-853 739 583 573 9 DNKS 7 7 7 66 958 86778 DYNA 775 8-899 96 76693 ELTY 85-6 86 656 68396 GGRM 75 956 3 57 59 9367 7338899 3 GJTL 5 75-395 56353 6567 7355 HDTX 3-55 - 69 79-5633 86339 5 HMSP 575 3 936 678 396 97768 6 IKAI 5-88 - 7 7863-769 79 7 IMAS 63-37 56 33 35 8 INDF 775 7 8 598 5575 8795 53885 9 INTA 95 5-75 9877 37 65566 INTD 55 9-6 -65-69 3536 INTP 5 8-5 387 8376 566 KLBF 7-56 5768 566335 839 3 MERK 58 75 677 683 38 SMCB 385 3-36 35-3795 766 5 SMSM 75 37 35 95 5879 8955 636 6 UNVR 365 7 8 53 688 7776 3676 7 NIPS 3 9-58 93 856 773 8 MDRN 55-5 -87 9 536 9 DVLA 75 83-5 6797 7878 373559 3 LTLS 75 58 95 556 87 3 MIRA - 76 797-767 83989 3 MYOR 975-66 837 59 8779 33 SMDR 55 6 5 57 39995 9777 55 3 SMGR 8 68 5 57 738 99 656 35 SMRA 95 66 8 773 9693 7796 36 STTP - 9-79 9656 5557 37 TSPC 9 77 36 3766 38976 9335 38 TURI 3 58 6 3-5935 5767 855 39 ZBRA 65 3-5 6 38 89 3

NO PERUSH MV EARN DIV CFO LB.USAHA TOT.ASS ACAP 6 5-678 9 933 ADES 9-85 - -638-69857 977 3 AQUA 5 696-789 868 6757 679 BATA 7 697-33 566 698 6535 5 BKSL 75-5 - 78 53-3695 76763 6 BRPT - - 389 879 3989 338386 7 CMPP 5-7 8 36 85 795 8 CTRS 8 77 5 895 8988 6337 557 9 DNKS 97 6 3 766 857 5887 DYNA 67 53-57 9867 998 9988 ELTY 65 6-935 57 737 99 GGRM 5 93-6339 8368 986 59389 3 GJTL 86 5-53 5938 68377 637 HDTX 5-9 - 5 589-663 378 5 HMSP 3 5-8 8755 38378 56395 6 IKAI 5-8 -75 69 7538 7 IMAS 7-57 - 366 87 87656 8788 8 INDF 98-38 83879 8739 56698 9 INTA 5 3-783 5897 875 78 INTD 95 6-58 85 3335 INTP 35 3-58 33966 83637 977 KLBF 7 6-6 573 733589 3686 3 MERK 55 555-86 55 898 66 SMCB 59-7 - 8 5-69983 753 5 SMSM 35 35 87 959 87 6593 6 UNVR 385 9-77 5869 3998 366379 7 NIPS - - 5 5987 8987 8 MDRN 6 - - 67 78 733 993 9 DVLA 7 89-67 55668 86 37 3 LTLS 7 67-678 -776 373 973 3 MIRA 8 - - 8 5 57 786 3 MYOR 3-53 373 363 865 33 SMDR 69 7 53 3395 35 57977 3 SMGR 58 877 37 68 8578 958 66 35 SMRA 98 78 5 353 7998 3399 789 36 STTP 9 9 3 73 787 777 37 TSPC 85 7-3998 898 3865 9 38 TURI 86 9 5-858 736 7879 39 ZBRA 65-6 9557 76 3537

Lampiran. Deskriptif Statistik, Uji Asumsi Klasik dan Regresi Variabel Dependen Deskriptif Statistik Descriptive Statistics MV Valid N (listwise) N Minimum Maximum Mean Std. Deviation 78 75 75 3.3 85.376 78 Variabel Independen Descriptive Statistics EARNINGS DIV Valid N (listwise) N Minimum Maximum Mean Std. Deviation 78-78 7.66 68.93 78 8.97 5.566 78. 6. 87.6 5.536 78 5

MVit = ao + ait + Uit Uji Normalitas Explore Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent 78 5.% 78 5.% 56.% Descriptives Mean 95% Confidence Interval for Mean Lower Bound Upper Bound Statistic Std. Error..579 -.3378.3378 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis -7.65 -.7539 38.533 78.993-5. 39.6883 6.7736 33.6788.93.7 -.6.538 Extreme Values Highest Lowest 3 5 3 5 Case Number Value 56 39.6883 6 387.967 3 37.6663 7 37.587 7 36.737 55-5. 6 -.59 8 -. -38.55 7-3.873 6

Tests of Normality Kolmogorov-Smirnov a Shapiro-Wilk Statistic df Sig. Statistic df Sig..99 78.55.9 78. a. Lilliefors Significance Correction Histogram 8 6 Frequency Std. Dev = 78.9 Mean =. N = 78. -5. -5. -5. 5. 5. 5. 35. -. -.... 3.. 3 Normal Q-Q Plot of Expected Normal - - -3-6 - - 6 Observed Value 7

.8 Detrended Normal Q-Q Plot of.6.. Dev from Normal. -. -. -3 - - 3 Observed Value 6 - - N = 78 Unstandardized Resid Uji Heteroskedastisitas Regression Descriptive Statistics ABS_ Mean Std. Deviation N 7.5765 99.73675 78 87.6 5.536 78 8

Correlations Pearson Correlation Sig. (-tailed) N ABS_ ABS_ ABS_ ABS_. -. -....3.3. 78 78 78 78 Variables Entered/Removed b Variables Variables Entered Removed Method a. Enter a. All requested variables entered. b. Dependent Variable: ABS_ Summary b Adjusted Std. Error of Durbin-W R R Square R Square the Estimate atson. a..3 98.6379.89 a. Predictors: (Constant), b. Dependent Variable: ABS_ Regression Residual Total a. Predictors: (Constant), b. Dependent Variable: ABS_ ANOVA b Sum of Squares df Mean Square F Sig. 3383.36 3383.36 3.5.65 a 7386. 76 963.7 76599.5 77 Unstandardized Coefficients Coefficients a Standardized Coefficients B Std. Error Beta t Sig. Tolerance VIF (Constant) 59.6.75.5. -.E-.7 -. -.87.65.. a. Dependent Variable: ABS_ Collinearity Statistics 9

Collinearity Diagnostics a Dimension a. Dependent Variable: ABS_ Condition Variance Proportions Eigenvalue Index (Constant).85..6.6.55.697.7.7 Predicted Value Residual Std. Predicted Value Std. Residual a. Dependent Variable: ABS_ Residuals Statistics a Minimum Maximum Mean Std. Deviation N -.7783 59.33 7.5765.9586595 78-56.637 39.93. 97.569776 78-7.7.55.. 78 -.596.5..993 78 Histogram Charts Dependent Variable: ABS_ 8 6 Frequency Std. Dev =.99 Mean =. N = 78. -.5 -. -.5..5..5..5 -.5 -.75 -.5.5.75.5.75.5 Regression Standardized Residual

Normal P-P Plot of Regression Standardized Residual. Dependent Variable: ABS_.75 Expected Cum Prob.5.5...5.5.75. Observed Cum Prob Uji Multikolinearitas, Uji Autokorelasi Regression Descriptive Statistics MV Mean Std. Deviation N 3.3 85.376 78 87.6 5.536 78 Pearson Correlation Sig. (-tailed) N Correlations MV MV MV MV..6.6..... 78 78 78 78 Variables Entered/Removed b Variables Variables Entered Removed Method a. Enter a. All requested variables entered. b. Dependent Variable: MV

Summary b Adjusted Std. Error of Durbin-W R R Square R Square the Estimate atson.6 a.69.56 8.8.7 a. Predictors: (Constant), b. Dependent Variable: MV Regression Residual Total a. Predictors: (Constant), b. Dependent Variable: MV ANOVA b Sum of Squares df Mean Square F Sig. 8396.8 8396.788 5.59. a 6657 76 39.698 665 77 Unstandardized Coefficients Coefficients a Standardized Coefficients Collinearity Statistics B Std. Error Beta t Sig. Tolerance VIF (Constant) 37.57 3.3 3.6. 3.3E-..6.365... a. Dependent Variable: MV Collinearity Diagnostics a Dimension a. Dependent Variable: MV Condition Variance Proportions Eigenvalue Index (Constant).85..6.6.55.697.7.7 Predicted Value Residual Std. Predicted Value Std. Residual a. Dependent Variable: MV Residuals Statistics a Minimum Maximum Mean Std. Deviation N 37.5 69. 3.3 8.537 78-5. 39.63. 78.99 78 -.55 7.7.. 78 -.389.8..993 78

Charts Histogram Dependent Variable: MV 8 6 Frequency Std. Dev =.99 Mean =. N = 78. -.5 -. -.5..5..5. -.5 -.75 -.5.5.75.5.75.5 Regression Standardized Residual Normal P-P Plot of Regression Standardized Residual. Dependent Variable: MV.75 Expected Cum Prob.5.5...5.5.75. Observed Cum Prob 3

MVit = bo + beit + vit Uji Normalitas Explore Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent 78 5.% 78 5.% 56.% Descriptives Mean 95% Confidence Interval for Mean Lower Bound Upper Bound Statistic Std. Error..57655 -.973.973 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis -5.533-3.77 33.75 8.77-9.83 37.5765 66.59 87.53.386.7 -.78.538 Extreme Values Highest Lowest 3 5 3 5 Case Number Value 3 37.5765 7 369.3755 7 363.98 6 36.56 39 355.996 63-9.83 55-68. -5.863 3-8.68 7-8.66

Tests of Normality Kolmogorov-Smirnov a Shapiro-Wilk Statistic df Sig. Statistic df Sig..97 78.66.95 78.6 a. Lilliefors Significance Correction Histogram 8 6 Frequency Std. Dev = 8.73 Mean =. N = 78. -3. -. -.... 3. -5. -5. -5. 5. 5. 5. 35. 3 Normal Q-Q Plot of Expected Normal - - -3-6 - - 6 Observed Value 5