Lampiran 8 : Hasil Statistik Deskriptif Lampiran 9 : Hasil Uji Asumsi Klasik Lampiran 10: Hasil Uji Regresi Linear Berganda
LAMPIRAN
Lampiran 1: Sampel Penelitian Perusahaan Otomotif dan Komponen yang Terdaftar di
Bursa Efek IndonesiaLampiran 2: Indikator yang menjadi Perhitungan
Lampiran 3: Perhitungan CR pada Perusahaan Perusahaan Otomotif dan Komponen
2012-2015
Lampiran 4: Perhitungan DER pada Perusahaan Perusahaan Otomotif dan Komponen
2012-2015
Lampiran 5: Perhitungan ITO pada Perusahaan Perusahaan Otomotif dan Komponen
2012-2015
Lampiran 6: Perhitungan ROE pada Perusahaan Perusahaan Otomotif dan Komponen
2012-2015
Lampiran 7: Perhitungan PER pada Perusahaan Perusahaan Otomotif dan Komponen
2012-2015Lampiran 8 : Hasil Statistik Deskriptif Lampiran 9 : Hasil Uji Asumsi Klasik Lampiran 10: Hasil Uji Regresi Linear Berganda
Lampiran 1
Sampel Penelitian Perusahaan Otomotif dan Komponen yang Terdaftar di Bursa
Efek Indonesia tahun 2012-2015
TANGGALNO KODE NAMA EMITEN
IPO
1 ASII PT. Astra Internasional Tbk 04-Apr-1990
2 AUTO PT. Astra Otoparts Tbk 15-Jun-1998
3 BRAM PT. Indo Kordsa Tbk 05-Sep-1990
4 GDYR PT. Goodyear Indonesia Tbk 01-Des-1980
5 GJTL PT. Gajah Tunggal Tbk 08-Mei-1990
6 IMAS PT. Indomobil Sukses International Tbk 15-Sep-1993
7 INDS PT. Indospring Tbk 10-Aug-1990
8 LPIN PT. Multi Prima Sejahtera Tbk 05-Feb-1990
9 MASA PT. Multistrada Arah Sarana Tbk 09-Jun-2005
10 NIPS PT. Nipres Tbk 24-Jul-1991
11 PRAS PT. Prima Alloy Steel Universal Tbk 12-Jul-1990
12 SMSM PT. Selamat Sempurna Tbk 09-Sep-1990
Lampiran 2
Indikator yang Menjadi Perhitungan
2012 2013 2014 2015 Aset LancarASII 75.799.000.000.000 88.352.000.000.000 97.241.000.000.000 105.161.000.000.000 AUTO 3.205.631.000.000 4.896.682.000.000 5.138.080.000.000 4.796.770.000.000 BRAM 830.921.425.130 1.110.241.641.888 1.354.185.778.896 1.401.392.741.954 GDYR 598.085.007.272 605.224.069.120 778.519.236.444 798.033.414.650 GJTL 5.194.057.000.000 6.843.853.000.000 6.283.252.000.000 6.602.281.000.000
IMAS 9.850.095.954.329 11.634.955.170.257 11.845.370.194.860 12.192.274.613.320
INDS 877.635.915.018 1.086.590.779.051 975.954.232.621 992.929.224.058 LPIN 95.726.263.363 117.583.929.998 84.882.248.725 142.576.406.096 MASA 1.644.677.115.662 1.968.790.111.456 2.074.069.835.196 2.183.557.239.758 NIPS 308.486.312.000 534.840.333.000 671.452.284.000 701.282.705.000 PRAS 197.198.600.380 331.855.600.868 566.779.211.419 658.889.212.539 SMSM 986.324.235.891 1.108.057.000.000 1.133.730.000.000 1.368.558.000.000 2012 2013 2014 2015 Utang Lancar
ASII 54.178.000.000.000 71.139.000.000.000 74.241.000.000.000 76.242.000.000.000 AUTO 2.751.766.000.000 2.661.312.000.000 3.857.809.000.000 3.625.907.000.000 BRAM 390.549.003.362 706.551.216.928 956.599.789.524 775.763.748.306 GDYR 668.388.304.224 644.948.059.680 824.455.479.804 852.087.981.140 GJTL 3.020.030.000.000 2.964.235.000.000 3.116.223.000.000 3.713.148.000.000
IMAS 7.963.486.975.807 10.720.516.169.124 11.473.255.532.702 13.035.531.353.729
INDS 371.743.866.089 281.799.219.289 335.123.443.361 445.006.853.182 LPIN 32.995.214.492 47.334.458.367 39.239.103.931 180.556.111.049 MASA 1.180.412.892.636 1.266.144.535.008 1.186.691.002.818 1.699.064.633.222 NIPS 278.822.186.000 508.836.644.000 518.954.801.000 669.595.797.000 PRAS 177.151.899.038 321.945.837.163 564.899.086.298 655.589.698.468 SMSM 480.851.511.068 524.654.000.000 536.800.000.000 571.712.000.000
2012 2013 2014 2015 ASII 92.460.000.000.000 107.806.000.000.000 115.840.000.000.000 118.902.000.000.000 AUTO 3.396.543.000.000 3.058.924.000.000 4.244.862.000.000 4.195.684.000.000 BRAM 583.547.165.960 923.755.158.816 1.616.909.113.590 1.494.772.943.566 GDYR 684.942.445.258 664.884.345.024 858.313.951.554 876.182.546.636 GJTL 7.391.409.000.000 9.626.411.000.000 10.485.032.000.000 12.115.363.000.000
IMAS 11.869.218.951.856 15.655.152.396.933 16.753.973.180.065 18.163.865.982.392
INDS 528.206.496.386 443.652.749.965 459.998.606.660 634.889.428.231 LPIN 37.413.214.492 52.980.206.367 48.626.571.931 207.564.071.081 MASA 2.429.583.028.886 3.077.923.108.608 3.113.850.675.936 3.472.371.951.378 NIPS 322.620.214.000 562.461.853.000 624.632.294.000 938.717.411.000
PRAS 297.056.156.250 389.182.140.905 601.006.310.349 811.177.918.367 SMSM 646.095.282.949 695.957.000.000 635.514.000.000 779.860.000.000 Total Utang 2012 2013 2014 2015
ASII 89.814.000.000.000 106.188.000.000.000 120.187.000.000.000 126.533.000.000.000 AUTO 5.485.099.000.000 9.425.919.000.000 10.142.706.000.000 10.143.426.000.000 BRAM 1.632.114.305.314 1.975.181.227.872 2.199.454.519.116 2.510.949.078.006 GDYR 507.370.869.624 681.907.787.968 700.491.542.724 761.546.988.902 GJTL 5.478.384.000.000 5.724.343.000.000 5.637.004.000.000 5.394.142.000.000
IMAS 5.708.445.072.505 6.659.870.110.697 6.719.823.608.395 6.697.091.857.105
INDS 1.136.572.861.829 1.752.865.614.508 1.822.667.471.833 1.919.038.917.988 LPIN 134.855.613.501 143.410.609.857 132.155.190.760 116.490.714.202 MASA 3.579.220.252.804 4.551.387.301.888 4.628.740.449.684 4.741.667.755.684 NIPS 202.073.660.000 235.945.772.000 582.222.106.000 609.002.679.000 PRAS 280.293.729.818 406.448.113.303 685.821.589.456 720.564.133.797 SMSM 910.119.059.264 1.016.753.000.000 1.122.120.000.000 1.440.248.000.000 Modal Sendiri
2012 2013 2014 2015 ASII 188.053.000.000.000 193.880.000.000.000 201.701.000.000.000 184.196.000.000.000 AUTO 8.277.485.000.000 10.701.988.000.000 12.255.427.000.000 11.723.787.000.000 BRAM 1.675.538.304.716 2.427.635.430.112 2.571.121.595.388 2.853.176.224.122 GDYR 1.957.137.652.250 2.236.157.001.600 1.989.950.061.216 2.119.286.603.632 GJTL 12.578.596.000.000 12.352.917.000.000 13.070.734.000.000 12.970.237.000.000
IMAS 19.780.838.058.900 20.094.736.395.135 19.458.165.173.088 18.099.979.783.215
INDS 1.476.987.701.603 1.702.447.098.851 1.866.977.260.105 1.659.505.639.261 LPIN 68.736.656.643 77.231.127.337 70.155.464.867 77.790.171.689 MASA 3.087.521.302.278 3.928.155.954.336 3.491.126.595.348 3.253.367.458.404 NIPS 702.719.255.000 911.064.069.000 1.015.868.035.000 987.862.829.000 PRAS 310.224.018.731 316.174.631.298 445.664.542.004 469.645.085.526 SMSM 2.269.289.777.481 2.381.889.000.000 2.632.860.000.000 2.802.924.000.000 Penjualan 2012 2013 2014 2015
ASII 15.285.000.000.000 14.433.000.000.000 16.986.000.000.000 18.337.000.000.000 AUTO 1.155.235.000.000 1.472.428.000.000 1.718.663.000.000 1.749.263.000.000 BRAM 354.116.464.624 510.124.891.872 656.001.099.276 716.871.302.130 GDYR 245.371.843.994 288.597.900.128 379.396.184.166 360.830.666.490 GJTL 1.478.827.000.000 1.820.112.000.000 2.247.074.000.000 2.112.616.000.000
IMAS 3.888.214.740.154 4.498.533.194.624 3.366.038.875.959 2.818.952.958.749
INDS 528.533.039.343 383.515.708.536 478.330.720.924 538.841.439.260 LPIN 26.665.573.944 46.082.485.435 53.259.970.197 39.606.789.768 MASA 917.190.939.672 1.040.199.931.392 1.081.389.883.836 974.802.662.474 NIPS 123.127.075.000 193.146.288.000 225.074.574.000 246.439.073.000 PRAS 119.894.122.220 153.754.605.992 205.840.908.489 286.994.128.546 SMSM 424.597.061.201 401.681.000.000 432.027.000.000 560.755.000.000 Persediaan
2012 2013 2014 2015 ASII 22.742.000.000.000 22.297.000.000.000 22.131.000.000.000 15.613.000.000.000
IMAS 899.090.885.530 621.139.761.829 -67.093.347.900 -22.489.430.531
66 BRAM 358,9006 129,7696 394,8582 317,0706 GDYR 1539,52 1334,08 84,1704 -4,1178 GJTL 325
21 PRAS 26,5 18,8 18,8 9,2 SMSM 152 214 271 297 EPS
33
47
INDS 422,80 279,62 193,27 1,44 LPIN 781 403 -478 -831 MASA 28,866 485,12 86,646 -4117,8 NIPS 1081
35 81,22 -89,92
ASII 480 480 474 357 AUTO 264 209 180
AUTO 1.135.914.000.000 999.766.000.000 954.086.000.000 322.701.000.000 BRAM 216.940.652.552 67.216.650.560 203.332.118.688 172.585.315.956 GDYR 64.217.199.134 56.205.894.048 34.417.920.216 -1.523.284.028 GJTL 1.132.247.000.000 120.330.000.000 283.016.000.000 -313.326.000.000
SMSM 2525 3450 4750 4760 Harga Saham 2012 2013 2014 2015
INDS 3924 2140 1600 350 LPIN 7650 5000 6200 5375 MASA 450 390 420 351 NIPS 113 323 487 425 PRAS 255 185 204 125
IMAS 5300 4900 4000 2365
ASII 7600 6800 7425 6000 AUTO 3548 3650 4200 1600 BRAM 3000 2250 5000 4680 GDYR 1230 1900 1600 2725 GJTL 2225 1680 1425 530
PRAS 15.565.386.865 13.196.638.424 11.340.527.608 6.437.333.237 SMSM 286.929.498.426 352.701.000.000 421.095.000.000 461.307.000.000 Laba Bersih setelah pajak 2012 2013 2014 2015
INDS 134.068.283.255 147.608.449.013 127.819.512.585 1.933.819.152 LPIN 16.599.848.712 8.554.996.356 -9.416.233.847 -18.173.655.308 MASA 3.076.605.634 43.679.780.320 6.809.088.288 -368.667.635.998 NIPS 21.610.141.000 33.872.112.000 49.741.721.000 30.671.339.000
IMAS 289,93 192,55 -45,72 -16,54
Lampiran 3
Perhitungan CR pada Perusahaan Otomotif dan Komponen tahun 2012-2015
2012 2013 2014 2015ASII 1,399 1,242 1,310 1,379 AUTO 1,165 1,840 1,332 1,323 BRAM 2,128 1,571 1,416 1,806 GDYR 0,895 0,938 0,944 0,937
GJTL 1,720 2,309 2,016 1,778
IMAS 1,237 1,085 1,032 0,935
INDS 2,361 3,856 2,912 2,231 LPIN 2,901 2,484 2,163 0,790 MASA 1,393 1,555 1,748 1,285 NIPS 1,106 1,051 1,294 1,047
PRAS 1,113 1,031 1,003 1,005 SMSM 2,051 2,112 2,112 2,394 CR
Lampiran 4
Perhitungan DER pada Perusahaan Otomotif dan Komponen tahun 2012-2015
2012 2013 2014 2015 ASII 1,029 1,015 0,964 0,940 AUTO
0,619 0,325 0,419 0,414 BRAM 0,358 0,468 0,735 0,595 GDYR 1,350 0,975 1,225 1,151
GJTL 1,349 1,682 1,860 2,246
IMAS 2,079 2,351 2,493 2,712
INDS 0,465 0,253 0,252 0,331 LPIN 0,277 0,369 0,368 1,782 MASA 0,679 0,676 0,673 0,732 NIPS 1,597 2,384 1,073 1,541
PRAS 1,060 0,958 0,876 1,126 SMSM 0,710 0,684 0,566 0,541 DER
Lampiran 5 Perhitungan ITO pada Perusahaan Otomotif dan Komponen tahun 2012-2015 2012 2013 2014 2015 ASII 12,303 13,433 11,875 10,045 AUTO 7,165 7,268 7,131 6,702
BRAM 4,732 4,759 3,919 3,980 GDYR 7,976 7,748 5,245 5,873 GJTL 8,506 6,787 5,817 6,139
IMAS 5,087 4,467 5,781 6,421
INDS 2,795 4,439 3,903 3,080 LPIN 2,578 1,676 1,317 1,964 MASA 3,366 3,776 3,228 3,337 NIPS 5,707 4,717 4,513 4,009
PRAS 2,587 2,056 2,165 1,636 SMSM 5,345 5,930 6,094 4,998
ITO
Lampiran 6
Perhitungan ROE pada Perusahaan Otomotif dan Komponen tahun 2012-2015
2012 2013 2014 2015ASII 0,253 0,210 0,184 0,123 AUTO 0,207 0,106 0,094 0,032 BRAM 0,133 0,034 0,092 0,069 GDYR 0,127 0,082 0,049 -0,002
INDS 0,118 0,084 0,070 0,001 LPIN 0,123 0,060 -0,071 -0,156 MASA 0,001 0,010 0,001 -0,078 NIPS 0,107 0,144 0,085 0,050
PRAS 0,056 0,032 0,017 0,009 SMSM 0,315 0,347 0,375 0,320
ROE
GJTL 0,207 0,021 0,050 -0,058
Lampiran 7 Perhitungan PER pada Perusahaan Otomotif dan Komponen tahun 2012-2015 2012 2013 2014 2015 ASII 15,833 14,167 15,665 16,807 AUTO 13,439 17,464 23,333 24,242
BRAM 8,359 17,338 12,663 14,760 GDYR 0,799 1,424 19,009 -661,761
GJTL 6,846 48,000 17,545 -5,894
INDS 9,281 7,653 8,279 243,056 LPIN 9,795 12,407 -12,971 -6,468 MASA
15,589 0,804 4,847 -0,085 NIPS 0,105 6,872 14,758 20,238 PRAS 9,623 9,840 10,851 13,587
SMSM 16,612 16,121 17,528 16,027 PER
Lampiran 8 Hasil Statistik Desktiptif
1. Statistik Deskriptif Sebelum Normalitas Descriptive Statistics
N Minimum Maximum Mean Std. Deviation CR 48 ,790 3,856 1,59865 ,647700 DER 48 ,252 2,712 1,02765 ,664685
ITO 48 1,317 13,433 5,29948 2,720027 ROE 48 -,156 ,375 ,08898 ,110172 PER 48 -661,761 243,056 -2,54919 106,729233 Valid N (listwise)
48
2. Statistik Deskriptif Setelah Normalitas Descriptive Statistics
N Minimum Maximum Mean Std. Deviation CR 44 ,790 3,856 1,62727 ,648469 DER 44 ,252 2,384 ,96909 ,593162
ITO 44 1,317 13,433 5,30045 2,816013 ROE 44 -,156 ,375 ,09739 ,111345 PER 44 -12,971 48,000 11,97318 9,981184 Valid N (listwise)
44
Lampiran 9
Hasil Uji Asumsi Klasik
One-Sample Kolmogorov-Smirnov Test
Kolmogorov-Smirnov Z ,591 Asymp. Sig. (2-tailed) ,876 a. Test distribution is Normal.
Most Extreme Differences Absolute ,089 Positive ,089 Negative -,077
0E-7 Std. Deviation 9,32965936
Mean
a,b
44 Normal Parameters
N
Unstandardized Residual
b. Calculated from data.
1. Uji Normalitas Uji Normalitas Awal
Kolmogorov-Smirnov Z 1,921 Asymp. Sig. (2-tailed) ,001 a. Test distribution is Normal.
Most Extreme Differences Absolute ,277 Positive ,276 Negative -,277
0E-7 Std. Deviation 102,68022172
Mean
a,b
48 Normal Parameters
N
Unstandardized Residual
2. Uji Normalitas Akhir One-Sample Kolmogorov-Smirnov Test
b. Calculated from data.
Outlier
2. Uji Multtikolonieritas Coefficients a
Model Unstandardized Coefficients
Standardized Coefficients t Sig.
Collinearity Statistics B Std.
Error Beta Tolerance
VIF 1 (Constant) 3,849 7,196 ,535 ,596 CR 1,043 2,743 ,068 ,380 ,706 ,706 1,417 DER 1,561 2,901 ,093 ,538 ,594 ,754 1,326
ITO ,518 ,645 ,146 ,803 ,427 ,677 1,476 ROE 22,285 16,450 ,249 1,355 ,183 ,665 1,503
a. Dependent Variable: PER
3. Uji Heteroskedastisitas Uji Glejser Coefficients a
Model Unstandardized Coefficients
Standardized Coefficients t Sig. Kesimpulan
B Std. Error Beta 1 (Constant) -2,383 3,832 -,622 ,538 CR 2,704 1,460 ,272 1,852 ,072 Tidak Terjadi Heteroskedastisitas DER 4,185 1,544 ,386 2,710 ,010 Terjadi Heteroskedastisitas
ITO ,761 ,343 ,333 2,218 ,032 Terjadi Heteroskedastisitas ROE -35,262 8,759 -,610 -4,026 ,000 Terjadi Heteroskedastisitas
a. Dependent Variable: uji_glejser
Uji Korelasi Spearman
Correlations
CR DER
ITO ROE Absres Spearman's rho
Correlation Coefficient 1,000 -,634 -,060 ,185 -,271
- Sig. (2-tailed) . ,000 ,700 ,229 ,075
CR N
44
44
44
44
44
Correlation Coefficient -,634 1,000 ,203 -,059 ,327 DER Sig. (2-tailed) ,000 . ,185 ,705 ,030
N
44
44
44
44
44
- Correlation Coefficient -,060 ,203 1,000 ,583 ,095
ITO Sig. (2-tailed) ,700 ,185 . ,000 ,538 N
44
44
44
44
44
Correlation Coefficient ,185 -,059 ,583 1,000 -,496 ROE Sig. (2-tailed) ,229 ,705 ,000 . ,001
N
44
44
44
44
44
Correlation Coefficient -,271 ,327 ,095 -,496 1,000 Absres Sig. (2-tailed) ,075 ,030 ,538 ,001 .
N
44
44
44
44
44 **. Correlation is significant at the 0.01 level (2-tailed).
- . Correlation is significant at the 0.05 level (2-tailed).
Transformasi Heteroskedastisitas
a CoefficientsUnstandardized Standardized Coefficients Coefficients
Model t Sig.
B Std. Error Beta
1 (Constant) 11,328 2,939 3,855 ,000
INVERSE_DER ,665 2,594 ,040 ,256 ,799
a. Dependent Variable: PER
a
Coefficients
Model Unstandardized Standardized t Sig.Coefficients Coefficients B Std. Error Beta 1 (Constant) 9,169 1,925 4,763 ,000
INVERSEROE 28,792 13,099 ,321 2,198 ,034
a. Dependent Variable: PER
4. Uji Autokorelasi b Model Summary
Model R R Square Adjusted R Std. Error of the Durbin-Watson Square Estimate
a
1 ,355 ,126 ,037 9,796427 1,779
a. Predictors: (Constant), ROE, DER, CR, ITO
b. Dependent Variable: PER
Lampiran 10 Uji Regresi Linear Berganda Coefficients a
Model Unstandardized Coefficients
Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3,849 7,196 ,535 ,596
CR 1,043 2,743 ,068 ,380 ,706 DER 1,561 2,901 ,093 ,538 ,594
ITO ,518 ,645 ,146 ,803 ,427 ROE 22,285 16,450 ,249 1,355 ,183
a. Dependent Variable: PER
Filename:
Skripsi_13.30.0121_Thio,Kori_Karunia_O_PENGARUH_CURRENT_RATIO,DEBT_TO_EQUITY_RATIO,INVENTORY_TURNOVER_DAN_RET
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=====================1/62====================== PENGARUH CURRENT RATIO, DEBT TO EQUITY RATIO,
INVENTORY TURNOVER DAN RETURN ON EQUITY TERHADAP PRICE EARNING RATIO (Studi Empiris Pada Perusahaan Otomotif dan Komponen Yang Terdaftar Di Bursa Efek Indonesia Periode 2012-2015) SKRIPSI Diajukan untuk memenuhi syarat guna mencapai gelar Sarjana Ekonomi pada Program Studi Manajemen Fakultas Ekonomi dan Bisnis Universitas Katolik Soegijapranata Semarang Disusun oleh : Thio, Kori Karunia Odelia 13.30.0121 PROGRAM STUDI MANAJEMEN FAKULTAS EKONOMI DAN BISNIS UNIVERSITAS KATOLIK SOEGIJAPRANATA SEMARANG 2017 =====================2/62======================
BAB I PENDAHULUAN
1.1. Latar Belakang Kondisi perekonomian Indonesia terus mengalami perubahan pada tiga tahun terakhir ini. Hal ini dilihat dari tahun 2012-2014 pada masa pemerintahan Susilo Bambang Yudhoyono dan Jusuf Kalla, bahwa pertumbuhan perekonomian Indonesia mengalami penurunan. Badan Pusat Statistik mencatat bahwa pertumbuhan perekonomian Indonesia pada tahun 2012 sebesar 6,19 % mengalami penurunan pada tahun 2013 sebesar 5,56 % dan mengalami penurunan kembali menjadi 5,02 % pada tahun 2014. Hal yang sama juga terjadi pada masa pemerintahan Jokowi dan Jusuf Kalla. Menurut Badan Pusat Statistik pertumbuhan perekonomian Indonesia mengalami penurunan menjadi 4,79 % pada tahun 2015, hal tersebut disebabkan karena anjloknya konsumsi rumah tangga seperti: makanan jadi, minuman, rokok, dll. Dibawah ini merupakan data pertumbuhan ekonomi Indonesia pada lima tahun terakhir yaitu pada tahun 2010- 2015.
=====================3/62====================== Diagram 1.1. Pertumbuhan Ekonomi Indonesia tahun 2010-2015 Sumber : Badan Pusat Statistik Dengan adanya kondisi perekonomian Indonesia yang selalu mengalami ketidakpastian tersebut, tentunya akan berpengaruh besar terhadap seluruh sektor industri salah satunya adalah industri otomotif. Industri otomotif berperan penting dalam perekonomian nasional. Selain menyediakan angkutan penumpang dan barang, industri otomotif juga telah membuka lapangan kerja (http://www.gaikindo.or.id/). Menurut Basri (2016) Indonesia merupakan produsen otomotif terbesar kedua di ASEAN dan sebagai penyumbang dalam pendapat nasional. Tanpa adanya industri otomotif, maka perekonomian Indonesia akan terus mengalami gejolak. Untuk itu setiap perusahaan terkhusus industri otomotif harus mampu meningkatkan kemampuannya dalam melaksanakan efisiensi di semua aspek manajemen, salah satunya adalah aspek manajemen keuangan. Manajemen keuangan yang baik dapat dilihat dari kinerja suatu perusahaan. Oleh sebab itu, tujuan utama manajemen keuangan adalah untuk memaksimalkan harga saham =====================4/62====================== dan untuk memahami kinerja perusahaan dalam laporan keuangan, yang dapat dianalisis melalui analisis rasio keuangan. Analisis rasio keuangan merupakan alat untuk menganalisa keadaan atau posisi keuangan dalam perusahaan. Menurut Prihadi (2008) Analisis rasio