MODEL RESEARCH Data and Research Sample

III. MODEL RESEARCH Data and Research Sample

The data used in this research is secondary data obtained from the electronic media . The data used in this study originated of the financial statements of Islamic banks ( BUS ) quarterly during the period March 2011 until September 2015 , which can be accessed directly via Bank Indonesia website ( www.bi.go.id ) or the websites of the company's bank samples. This period was selected for the implementation of the laws of Islamic banks in Indonesia in accordance with Act No. 21 of 2008 concerning Islamic banking began to be implemented in 2008. Sampling was done by purposive sampling in order to get the samples according to specified criteria .

The conditions of samples used in this study are :

1) Islamic commercial bank national scale that publishes reports quarterly results for the period March 2011 until September 2015 which stated in rupiah ( IDR ) .

2) Data provided complete financial statements as a whole and in Inside are the data required in the study , namely Total financing ( total financing) , NPF (Non Performing Loan ) , EBTP (Earning Before Tax and Provision ) , PPAP ( Allowance for uncollectible earning assets ) , CAR ( Capital

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Adequacy Ratio) , total assets , and the age of Islamic banks which published the period December 2011 until September 2015 .

Variable Operational Research and Definitions In this study involving two variables, namely the dependent variable and independent variables. In addition, the independent variables are also variables control. dependent variables The dependent variable used in this study is a smoothing profit (income smoothing) are proxied by possible losses productive (PPAP). PPAP value obtained directly from published financial statements Islamic Bank. PPAP value on the quarterly financial statements of banks are progressive, in the sense of the quarterly financial reports submitted are quarterly progress reports for one year. Therefore, the value ofthis variable using the difference of the period by period previous. Independent variables Independent variables used in this study refers to the research Boulila et al, (2010) which had previously been used by Perez et al. (2008), which is the amount of financing that is proxied by total financing (TF), the financing risk is proxied by Non Performing Financing (NPF), and the profitability of Islamic banks are proxied by Earnings Before Taxes and Provisions (EBTP). TF value in the financial statements quarterly bank is progressive, in the sense quarterly financial reportis delivered quarterly progress reports for one year. By Hence the value of this variable using the difference of the period with previous period. Profitability is proxied by Earning before tax and provision was also obtained in the same manner except for a period of months March.

Total financing (TF) is used with the aim to showthe implementation of dynamic provisioning carried out by Islamic banks. TF a total financing provided Islamic bank, or formulated as follows:

TL = Total + Total Financing Receivables Islamic Sharia Murabaha Sharia receivables = receivables + receivables Istishna Islamic financing= Musharaka financing+ mudharabah financing NPF is used to reflect the credit risk, the smaller the NPF the smaller the credit risk borne by the bank. Banks

with NPF high will increase costs, better provisioning of productive assets and other costs, so the potential for bank losses (Mawardi, 2005). This variable is already listed on the published financial statements of the bank. Furthermore, to determine the smoothing Islamic banks profit , first performed an examination of the variability of the object income smoothing , which is the ratio coefficient of variation of the change in net income (net income) with a coefficient of variation of changes in the amount of operating income ( Total sales) . The test is performed using coefficients Eckel as was done in previous research by Boulila , et al . (2010 ) .Eckel coefficient is calculated by dividing the value of the standard deviation rate of change in earnings by the average value of the net profit ( EBTP ) of Islamic Bank. In Masodah (2007 ) , also measured by income smoothing

Eckel index which is described as follows :

Indeks Eckel = CV ϪI CV ϪS EBTP = amount profit before tax + number of zakat That issued by bank+ the number of backup load PPAP

Then to analyze the factors that affect the objects income smoothing used multiple linear regression analysis . The shape of the model econometric used in this study was based on a study Pe'rez , et al . (2008 ) , and Boulila , et al . (2010 ) . The model is formulated as follows

: PPAPit = α + β1 TFit + β2 NPFit + ε PPAP = Earning Assets Allowance for general and special on bank i during the quarterly period t TF = Total Islamic financing given to the bank i during quarterly period t NPF = Ratio of Non Performin Financing ( credit crunch )

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IV . RESULTS AND DISCUSSION Descriptive statistics

Descriptive statistical analysis used to describe or a description of each of the variables involved in the study . Of the 11 banks sharia there was only nine Islamic banks that managed meet the criteria. Furthermore, the minimum value , maximum , average (mean ) value middle ( median ) and standard deviation ( δ ) of each study variable can be seen in Table 4.1 below :

Table 4.1: Descriptive Variables Research

N MINIMUM MAKSIMUM RATA

– NILAI

STANDAR

TENGAH DEVIASI INCOME

RATA

1,98 SMOOTHING The

1,83 financing Financing risks

amount of

2,05 source : secondary data that is processed2016

Based on the results of the calculations in Table 4.1 it can be seen that from 9 companies Islamic banks where there are 76 reports , used seven variables research. Variable income smoothing by proxy PPAP its average value ( mean) at 24.86 with a standard deviation ( SD ) of 1.98. then variable Total Financing by proxy total financing ( TF ) has an average value and standard deviation respectively by 27.07 and 1.83. variable risk financing by proxy of non-performing financing ( NPF ) has an average of 3.47 with a standard deviation of 2.05 . This shows that NPF value for the year is still within the maximum limit of the NPF required by Bank Indonesia at 5% .

Classic assumption test

1. Normality Test Data In this study , the normality test is done with a statistical test Kolmogorov - Smirnov . Statistical tests One

Sample Kolmogorov- Smirnov ( see table one sample Kolmogorov - Smirnov in the annex) shows the Kolmogorov - Smirnov Z value of 0.62 ; and asymp . sig . as big as 0.82. This means that the value is greater than 0.05 . Thus it can be concluded the residual value is normally distributed or qualified test normality .

2. Test Multikoliniaritas Multikolinearitas , one of which can be seen from the value of tolerance and opponent variance inflation

factor ( VIF ) . Cutoff values are frequently used for indicates multikolinearitas is the tolerance value < 0.10 or equal with VIF > 10 . The test results obtained showed regression model the values of tolerance and VIF for each variable as follows :

Table 4.2: Value Tolerance and VIF

Variabel

Colinierity statistic Tolerence VIF

Income smoothing

The amount of financing 0,59

Financing risk

Source: secondery data is proceeds 2016

Table 4.2 shows the value of tolerance for all independent variables in above 0.10 and VIF for all the independent variables are also under 10. It accordance with the terms non-occurrence of multicollinearity, so all The independent variables eligible for use in research.

3. Test Autocorrelation Autocorrelation in this study using a test Durbin-Watson (DW test). From the test results (see table in

appendix a model summary) obtained the value of DW (d) of 2.09. While the value du according to the table to sample (n) 76 with six independent variables (k = 6) is 1.80, so get the value du <d <4 - du. This value is conditional on the occurrence of autocorrelation.

4. Test Heteroskidastity

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To detect the presence or absence of heteroscedasticity in this study is to use the test glejser. Glejser test done by regression of the absolute value of the residual value of the variable X (the independent variable) are estimated to have a close relat ionship with i2 δ. test results heteroscedasticity (Glejser test) can be shown in table 4.4 as follows:

Table 4.3: T critical - test results Glejser Variabel

T kritis Sig

Income smoothing

The amount of financing 0.08

Financing risk

Source: secondery data 2016

Based on the results shown in table 4.3 if it appears that all independent variables showed significant results , so it can concluded that all independent variables did not happen heteroskedastisitas the error variance . Simultaneous Significance Test The statistical test F is basically used to indicate whether all independent or independent variables included in the model have jointly influence on the dependent variable . Below is a table simultaneous significance test results :

Table 4.4: Simultaneous Significance Test Results

Sig Regresion 237,89

Model

Sum of squares Df Mean square F

Source:secondery data 2016

From the calculation results obtained F value of 54.25 and a significance value $ 0.00. Due to the significant value of less than 5 %, then the hypothesis is accepted and significant influence of the five variables together to variable PPAP . From the test results it was concluded that the F variable number.

NO Bank name Indeks Eckel Information

1 Bank muamalat

Income smoothing

2 Mega syariah

Income smoothing

3 Syariah mandiri

Income smoothing

4 BRI syariah

Income smoothing

5 Bukopin syariah

6 Panin syariah

7 Victoria syariah

8 BNI syariah

Income smoothing

Income smoothing Jumlah bank income smoothing

9 BCA syariah

Jumlah bank non income smoothing 3

Source: secondery data 2016

Classification results using Eckel index showed that 9 Islamic banks surveyed by the number of financial statements by 76 data, there are six banks that are categorized perform income smoothing (smoothing profit) and three banks do not perform income smoothing (income smoothing). value index Eckel explains the magnitude of the coefficient of variation of the variables are calculated based on the standard deviation of each change in net income company. This shows that Islamic banks have to grade profits are used to reduce the rate of change in net income in the reporting period.

Furthermore, other Hypothesis testing is done by testing partial regression equation of each independent variable Test using t-test. The t-test is intended to determine the effect partial (individual) independent variables (TF, NPF,) to variable income smoothing or test the significance of constant and the dependent variable. T's statistical results of this study can be seen in table following: