Berdasarkan simpulan diatas maka implikasi pada penelitian ini dapat dikemukakan sebagai berikut:
1. Bagi Pemerintah
Dalam penentuan kebijakan moneter, hendaknya pemerintah membuat kebijakan yang mendukung dan mendorong perbankan dalam meningkatkan kinerjanya.
2. Bagi Perbankan
Dalam penentuan kebijakan pengelolaan bank, para pengelola bank agar memerhatikan faktor fundamental makroekonomi yang ada dalam kebijakan Bank Indonesia yaitu pergerakan tingkat inflasi, BI rate dan kurs yang akan berpengaruh terhadap kinerja perbankan.
90 Selain ini pengelola bank juga harus berhati-hati dalam menentukan tingkat bunga kredit. Hal ini disebabkan besarnya tingkat bunga kredit akan berdampak pada tingkat penjualan kredit ke masyarakat dan akhirnya hal tersebut akan berpengaruh terhadap kinerja perbankan.
3. Bagi Investor
Kinerja perbankan sangat berguna untuk menimbang keuntungan yang akan di dapatoleh investor apabila investor ingin berinvestasi pada suatu perusahaan perbankan.
91
DAFTAR PUSTAKA
Abid, Lobna dan Med Nejib Ouertani dan Sonia Zouari-Ghorbel. Macroeconomic
and Bank-Specific Determinants of Household’s Non-Performing Loans in Tunisia: a Dynamic Panel Data. Procedia Economics and Finance 13 (2013): 58–68
Ali Shawtari, Fekri dan Buerhan Saiti dan Shaikh Hamzah Abdul Razak dan Mohamed Ariff. The impact of efficiency on discretionary loans/finance loss provision: A comparative study of Islamic and conventional banks. Borsa Istanbul Review 15-4 (2015): 272–282
Bank Indonesia. Laporan Perekonomian Indonesia tahun 2014. Diakses pada
Sabtu, 10 Oktober 2015 dari
http://www.bi.go.id/id/lip/laporan/Pages//Laporan-LIP-tahun-2014.aspx Bank Indonesia. Penjelasan BI Rate sebagai Suku Bunga Acuan. Diakses pada
Jumat, 10 Oktober 2015 dari http://www.bi.go.id/id/moneter/bi-rate/penjelasan/Contents/Default.aspx
Bank Indonesia. Pengenalan Inflasi. diakses pada Jumat, 10 Oktober 2015 dari http://www.bi.go.id/id/moneter/inflasi/pengenalan/Contents/Pentingnya.asp x
Bank Indonesia. Sejarah Bank Indonesia. Diakses pada Minggu, 15 Mei 2016 dari http://www.bi.go.id/id/tentang-bi/museum/sejarah-bi/pra-bi/Default.aspx Bank Indonesia. Statistik Perbankan Indonesia. Diakses pada Jumat, 29 Januari
2016 dari http://www.bi.go.id/id/statistik/perbankan/indonesia/Default.aspx Bank Indonesia. Surat Edaran No.13/1/PBI/2011 tentang Penilaian Tingkat
Kesehatan Bank Umum. Diakses pada Jumat, 10 Oktober 2015 dari
www.bi.go.id/peraturan/perbankan/Document/ae5182e22f2b4575ae1ff6012 973ea19pbi_132611a1.pdf
Bank Indonesia. Surat Edaran No.13/24/DPNP tanggal 25 Oktober 2011 tentang
Penilaian Tingkat Kesehatan Bank Umum. Diakses pada Sabtu, 24 Oktober
2015 dari
www.bi.go.id/id/peraturan/perbankan/Pages/SE%20No.13_24_DPNP_2011 .asp
Bank Indonesia. Suku Bunga Tabungan Rupiah menurut Kelompok Bank. Diakses
pada Jumat, 29 Januari2016 dari
92
Bank Mandiri. Profil Perusahaan. Diakses pada Minggu, 15 Mei 2016 dari http://www.bankmandiri.co.id/corporate01/about_profile.asp
Bank Negara Indonesia. Sejarah. Diakses pada Minggu, 15 Mei 2016 dari https://id.wikipedia.org/wiki/Bank_Rakyat_Indonesia
Bank Rakyat Indonesia. Sejarah BRI. Diakses pada Minggu, 15 Mei 2016 dari http://www.bri.co.id/articles/9
Bofondi, Marcello dan Tiziano Ropele. Macroeconomic determinants of bad loans: evidence from Italian banks. Occasional Papers No. 89, 2011.
Budianto, Totok dan Sigit Triandaru. Bank dan Lembaga Keuangan Lain Edisi 2. Jakarta: Salemba Empat, 2006.
Case, Karl E dan Ray C. Fair. Principles of Economics Eighth Edition. Jakarta: Penerbit Erlangga, 2007.
Cernohorska, Libena. Impact of Financial Crisis on the Stability Banking Sectors in the Czech Republic and Great Britain. Procedia Economics and Finance 26 (2015): 234–241
Florin Filip, Bogdan. The quality of bank loans within the framework of globalization. Procedia Economics and Finance 20(2015): 208–217
Hari Wijanto, Setyo. Metode Penelitian menggunakan Structural Equation
Modelling dengan LISREL 9. Jakarta: Lembaga Penerbit Fakultas Ekonomi
Universitas Indonesia, 2015.
Harmono. Faktor Fundamental Makro dan Skim Bunga Kredit sebagai Variabel
Intervening Pengaruhnya terhadap Kinerja Bank. Jurnal Keuangan dan Perbankan, Vol 16, No.1 Januari 2012.
Hidayat, Muhammad. Pengaruh Rasio Kesehatan Perbankan terhadap Nilai
Perusahaan (Studi Kasus pada Perbankan yang Terdaftar di Bursa Efek Indonesia). Jurnal Ekonomi dan Informasi Akuntansi (JENIUS), Januari, Vol 4, No. 1 2014.
https://pena.gunadarma.ac.id/perbandingan-tatacara-penilaian-tingkat-kesehatan-bank/ diakses pada 16 Oktober 2015
https://furqon95.wordpress.com/category/materi-kampus/ diakses pada Sabtu, 24 Oktober 2015
Jonas, Guilherme dan Livia Abrao. Basic Interest Rate, Bank Competition, and Bank Spread in Personal Credit Operations in Brazil: A Theoretical and Empirical Analysis. EconomiA 16(2015) 32-45
93
Kasmir. Manajemen Perbankan Edisi Revisi. Jakarta: PT. Raja Grafindo Persada, 2012.
Klein, Nir. Non-Performing Loans in CESEE: Determinants and Macroeconomic
Performance. IMF Working Paper No. 72, 2013.
Korkmaz, Suna. Impact of Bank Credits on Economic Growth and Inflation. Journal of Applied Finance & Banking, vol. 5, no. 1(2015): 51-63
Maria Caporale, Guglielmo danStefano Di Colli dan Juan Sergio Lopez. Bank Lending Procyclicality And Credit Quality During Financial Crises. Economics and Finance Working Paper No. 13-18, 2013.
Njorohe, Lucas dan Anne Wangari Kamau. Macroeconomic Developments and
Banks’ Behaviour in Kenya: A Panel Data Analysis. Saving and Development, N0. 2, XXXIV, 2010.
Ötker-Robe, İnci dan Jiri Podpiera. The Fundamental Determinants of Credit Default Risk for European Large Complex Financial Institutions. IMF Working Paper No. 153, 2010.
P. Louzis, Dimitros dan Angelos T. Vouldis dan Vasilios L. Metaxas. Macroeconomic and Bank-Specific Determinants of Non-Performing Loans in Greece: A Comparative Study of Mortgage, Business and Consumer Loan Portofolios. Economic Research Department – Special Studies Division Working Paper no 118, 2010.
Qasim, Syed dan Rizwan Jan. Analysis of Financial Performance of Private Banks in Pakistan. Procedia - Social and Behavioral Sciences 109 (2014) 1021-1025
Raluca Diaconu, Loana dan Dumitru-Cristian Oanea. Determinants of bank’s stability. Evidence from CreditCoop. Procedia Economics and Finance 32 (2015): 488-495
repository.usu.ac.id>bitstream diakses pada Sabtu, 24 Oktober 2015
Roman, Angela and Alina Camelia Sargu. The impact of bank-specific factors on the commercial banks liquidity: empirical evidence from CEE countries. Procedia Economics and Finance 20 (2015): 571–579
S. Mishkin, Frederic. The Economics of Money, Banking and Financial Markets Business School Edition (2nd edition). United States of America: Pearson Education, Inc 2010.
Santoso, Singgih. AMOS 22 untuk Structural Equation Modelling. Jakarta: PT. Elex Media Komputindo, 2015.
94
Sudiyatno, Bambang. Peran Kinerja Perusahaan dalam Menentukan Pengaruh
Faktor Fundamental Makroekonomi, Risiko Sistematis, dan Kebijakan Perusahaan Terhadap Nilai Perusahaan. Disertasi Universitas Diponegoro, Semarang, 2010.
Sufian, Fadzlan dan Muzafar Shah Habibillah. Assesing the Impact of Financial
Crisis on Bank Performance: Empirical Evidence from Indonesia. ASEAN
Economic Bulletin Vol.27, No. 3, 2010.
Sugiyono. Metode Penelitian Bisnis Kuantitatif, Kualitatif dan R&D. Bandung: CV. Alfabeta, 2011.
Thomas Olajide, Olubayo dan Taiwo Asaolu dan Charles Ayodele Jegede. The Impact of Financial Sector Reforms on Bank Performance in Nigeria. The International Journal of Business and Finance Research Vol. 5 No. 1, 2011. Tiberiu Albulescu, Claudiu. Bank’s Profitability and Financial Soundness
Indicators: A Macro-Level Investigation in Emerging Countries. Procedia - Economics and Finance 23 (2015): 203-209
Tri Siswanto, Budi. Pengembangan Model Penyelenggaraan Work-Based
Learning pada Pendidikan Vokasi Diploma III Otomatif. Disertasi
Universitas Negeri Yogyakarta, 2011.
Wahyudi, Untung dan Hartini P. Pawestri. Implikasi Struktur Kepemilikan Terhadap Nilai Perusahaan Dengan Keputusan Keuangan Sebagai Variabel Intervening. Padang: Simposium Nasional Akuntansi IX 2006. Wikipedia. Bank Negara Indonesia. Diakses pada Minggu, 15 Mei 2016 dari
https://id.wikipedia.org/wiki/Bank_Negara_Indonesia
Wikipedia. Bank Rakyat Indonesia. Diakses pada Minggu, 15 Mei 2016 dari https://id.wikipedia.org/wiki/Bank_Rakyat_Indonesia
Wikipedia. Bank Tabungan Negara. Diakses pada Minggu, 15 Mei 2016 dari https://id.wikipedia.org/wiki/Bank_Tabungan_Negara
95 LAMPIRAN
Lampiran 1 Output LISREL (Sebelum Modifikasi)
DATE: 3/27/2016 TIME: 17:53 L I S R E L 8.30 BY
Karl G. Jöreskog & Dag Sörbom This program is published exclusively by Scientific Software International, Inc. 7383 N. Lincoln Avenue, Suite 100 Chicago, IL 60646-1704, U.S.A.
Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140 Copyright by Scientific Software International, Inc., 1981-99 Use of this program is subject to the terms specified in the Universal Copyright Convention.
Website: www.ssicentral.com
The following lines were read from file Z:\E\AJENG1\SEM.SPJ:
Observed Variables
INF BIRATE KURS KMK KI KK NPL LDR ROA NIM CAR
Correlation Matrix From File Z:\E\AJENG1\SEM~~92F.COR Sample Size = 156
96 Relationships
INF BIRATE KURS = FM KMK KI KK = JPK
NPL LDR ROA NIM CAR = KP JPK = FM
KP = JPK Path Diagram
options ME=UL ADD=OFF IT=500 EF
set error covariance between BIRATE and INF to 0.5 set error covariance between BIRATE and KURS to 0.1 set error covariance between KURS and INF to 0.2 set error covariance between NIM and NPL to 0.2 !set error covariance between KK and KI to 0.01 !set error covariance between CAR and NPL to 0.1 !set error covariance between ROA and NPL to 0.1 !set error covariance between LDR and ROA to 0.001 !set error covariance between LDR and KK to 0.2 set error covariance between INF and NPL to 0.2 !set error covariance between INF and ROA to 0.1 !set error covariance between KI and KMK to 0.01 !set error covariance between KK and KMK to 0.01 !set error covariance between CAR and LDR to 0.001 !set error covariance between NIM and KURS to 0.2 !set error covariance between NIM and KURS to 0.01 set error variance JPK equal to free
set error variance KP equal to free End of Problem
97 Sample Size = 15
Correlation Matrix to be Analyzed
KMK KI KK NPL LDR ROA --- --- --- --- --- --- KMK 1.00 KI 0.97 1.00 KK 0.94 0.96 1.00 NPL 0.58 0.67 0.68 1.00 LDR -0.93 -0.93 -0.95 -0.60 1.00 ROA -0.75 -0.77 -0.74 -0.75 0.72 1.00 NIM -0.70 -0.60 -0.51 -0.10 0.56 0.38 CAR 0.71 0.73 0.71 0.56 -0.80 -0.50 INF 0.46 0.49 0.41 0.62 -0.38 -0.59 BIRATE 0.84 0.81 0.74 0.65 -0.71 -0.74 KURS -0.36 -0.32 -0.53 -0.30 0.50 0.24
Correlation Matrix to be Analyzed
NIM CAR INF BIRATE KURS --- --- --- --- ---
NIM 1.00
CAR -0.54 1.00
INF -0.28 0.41 1.00
98
KURS -0.03 -0.32 0.07 -0.11 1.00 Number of Iterations = 17
LISREL Estimates (Unweighted Least Squares)
KMK = 0.97*JPK, Errorvar.= 0.056, R² = 0.94 (0.13) 0.43 KI = 0.98*JPK, Errorvar.= 0.049, R² = 0.95 (0.052) (0.13) 18.80 0.39 KK = 0.96*JPK, Errorvar.= 0.087, R² = 0.91 (0.051) (0.13) 18.62 0.69 NPL = 0.71*KP, Errorvar.= 0.50 , R² = 0.50 (0.12) 4.14 LDR = - 0.94*KP, Errorvar.= 0.11 , R² = 0.89 (0.081) (0.13) -11.68 0.89 ROA = - 0.80*KP, Errorvar.= 0.36 , R² = 0.64 (0.071) (0.12)
99 -11.35 2.94 NIM = - 0.60*KP, Errorvar.= 0.64 , R² = 0.36 (0.061) (0.12) -9.79 5.50 CAR = 0.77*KP, Errorvar.= 0.40 , R² = 0.60 (0.070) (0.12) 11.06 3.36 INF = 0.48*FM, Errorvar.= 0.77 , R² = 0.23 (0.031) (0.12) 15.34 6.53 BIRATE = 0.84*FM, Errorvar.= 0.29 , R² = 0.71 (0.033) (0.13) 25.22 2.34 KURS = - 0.38*FM, Errorvar.= 0.86 , R² = 0.14 (0.031) (0.12) -12.03 7.44
Error Covariance for NIM and NPL = 0.20 Error Covariance for INF and NPL = 0.20 Error Covariance for BIRATE and INF = 0.50 Error Covariance for KURS and INF = 0.20
100 Error Covariance for KURS and BIRATE = 0.10
JPK = 1.00*FM,, R² = 1.00 (0.034) 29.06 KP = 1.00*JPK,, R² = 1.00 (0.044) 22.82
Correlation Matrix of Independent Variables
FM --- 1.00
Covariance Matrix of Latent Variables
JPK KP FM --- --- --- JPK 1.00
KP 1.00 1.00
101
Lampiran 2 Output LISREL (Setelah Modifikasi)
Goodness of Fit Statistics
Degrees of Freedom = 44
Normal Theory Weighted Least Squares Chi-Square = 59.99 (P = 0.055) Estimated Non-centrality Parameter (NCP) = 15.99
90 Percent Confidence Interval for NCP = (0.0 ; 40.38)
Minimum Fit Function Value = 0.39
Population Discrepancy Function Value (F0) = 0.10 90 Percent Confidence Interval for F0 = (0.0 ; 0.26)
Root Mean Square Error of Approximation (RMSEA) = 0.048 90 Percent Confidence Interval for RMSEA = (0.0 ; 0.077) P-Value for Test of Close Fit (RMSEA < 0.05) = 0.51
Expected Cross-Validation Index (ECVI) = 0.67 90 Percent Confidence Interval for ECVI = (0.57 ; 0.83) ECVI for Saturated Model = 0.85
ECVI for Independence Model = 22.19
Chi-Square for Independence Model with 55 Degrees of Freedom = 3418.06 Independence AIC = 3440.06
Model AIC = 103.99 Saturated AIC = 132.00 Independence CAIC = 3484.61 Model CAIC = 193.09
102 Saturated CAIC = 399.29
Root Mean Square Residual (RMR) = 0.077 Standardized RMR = 0.077
Goodness of Fit Index (GFI) = 0.99
Adjusted Goodness of Fit Index (AGFI) = 0.98 Parsimony Goodness of Fit Index (PGFI) = 0.66
Normed Fit Index (NFI) = 0.98 Non-Normed Fit Index (NNFI) = 0.99 Parsimony Normed Fit Index (PNFI) = 0.79 Comparative Fit Index (CFI) = 1.00 Incremental Fit Index (IFI) = 1.00 Relative Fit Index (RFI) = 0.98
Critical N (CN) = 178.53
The Modification Indices Suggest to Add an Error Covariance Between and Decrease in Chi-Square New Estimate CAR LDR 8.2 -0.71
INF ROA 8.1 -0.26 KURS NIM 11.1 -0.28
103 Total and Indirect Effects
Total Effects of KSI on ETA
FM --- JPK 1.00 (0.03) 29.06 KP 1.00 (0.03) 29.51
Indirect Effects of KSI on ETA
FM --- JPK - - KP 1.00 (0.03) 29.51
104 Total Effects of ETA on ETA
JPK KP --- --- JPK - - - - KP 1.00 - - (0.04) 22.82
Largest Eigenvalue of B*B' (Stability Index) is 1.000
Total Effects of ETA on Y
JPK KP --- --- KMK 0.97 - - KI 0.98 - - (0.05) 18.80 KK 0.96 - -
105 (0.05) 18.62 NPL 0.71 0.71 (0.03) 22.82 LDR -0.94 -0.94 (0.06) (0.08) -14.75 -11.68 ROA -0.80 -0.80 (0.06) (0.07) -13.84 -11.35 NIM -0.60 -0.60 (0.05) (0.06) -11.50 -9.79 CAR 0.77 0.77 (0.06) (0.07) 13.45 11.06
Indirect Effects of ETA on Y
106 --- --- KMK - - - - KI - - - - KK - - - - NPL 0.71 - - (0.03) 22.82 LDR -0.94 - - (0.06) -14.75 ROA -0.80 - - (0.06) -13.84 NIM -0.60 - - (0.05) -11.50 CAR 0.77 - - (0.06) 13.45
107 Total Effects of KSI on Y
FM --- KMK 0.97 (0.03) 29.06 KI 0.98 (0.04) 27.80 KK 0.96 (0.04) 27.29 NPL 0.71 (0.02) 29.51 LDR -0.94 (0.06) -16.05 ROA -0.80 (0.05)
108 -14.90 NIM -0.60 (0.05) -11.92 CAR 0.77 (0.05) 14.41
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