41
that join sustainability award have high confidence in social and environmental performance and also because most participant use GRI as a guideline. This
research will conduct purposive or judgment sampling. Researcher determines several criteria to take sample:
1. The selected companies are companies which are categorized in Indonesian stock exchange.
2. The observed companies published annual report on the company website from 2011
– 2014. 3. The observed companies published sustainability reporting on company
website from 2011 – 2014.
4. The observed companies published the sustainability reporting separately or differently with annual report.
5. The observed companies used GRI as guidance for sustainability reporting From the criteria above the researcher can decrease the total population
that participated in sustainability report award 2012 until 2015 from 59 companies become 16 sampling companies . The total sustainability report and
annual report used in this research is from 2011 – 2014.
C. Data Collection Method
The data that used in this research is from secondary sources. Secondary data is data that already made by previous research or available in the library,
online journal, company website, case studies and we can find it in website or internet. The data obtained in this research are gathered from sustainability
report award website and companies website.
42
The research is categorized as longitudinal data or panel data. Panel data is method research that cross-sectional time series dimension that can enhance
quality and quantity data. Panel data method can defined the time frame of research.
The data sustainability reporting and company information such as ROA, DAR, and BOC can also obtained in company annual report which are published
in the company website. This research will examine 64 sustainability reporting and financial database from 16 selected companies that participated in Indonesia
sustainability award 2012 until 2015.
D. Analysis Method
This research will use content analysis research. The content analysis comprises of 64 sustainability reporting and financial statement analyzed, coded
and scored. The content analysis is to identify the disclosure of social information and environmental information under each theme. Every type of
information will get scored by numbers. The researcher will give zero if there is no disclosure of sustainability report and the researcher will give 1 if there an
disclosure of sustainability report. This research is conducted base on multiple regression analysis. The
variable are tested by using descriptive analysis and hypothesis test. For organized the data the researcher used a statistical Package the social sciences
SPSS 22
43
1. Descriptive Statistics
Descriptive statistics analysis test used in this research to analyze sample data in order to describe the data that already researcher collected.
The descriptive statistical testing obtains a picture or describe data that can be seen in mean, median, standard deviation, variance, maximum, minimum,
sum of square, range, etc.
2. Classic Assumptions
a. Normality Test
The purpose of normality test is to determine whether regression model variables are normally distributed or not. Normality test
conducted try to find out that inferential statistics to be used is a parametric or non-parametric.. There are two ways to finds its normal or
not, with statistical test and graph analysis Ghozali, 2013. The normality technique of kolmogorof-smirnof Z and shapiro-
Wilk uses to make decision making when the value Asymp.Sig. 2- tailed less than 0.05 5 it means the distribution is not normal but
if the value Asymp.Sig. 2-tailed more than 0.05 5 it means the distribution is normally distributed.
The graph analysis technique for normality test can be done by looking at the spread data dots on the diagonal axis of the graph or by
looking at the histogram from the residual. If the dots looks like a ring bell it means that the distribution is normal and if the dots is not look like
44
ring bell and do not follow the diagonal line it means that the distribution is not normal.
b. Heteroskidastity Test
According to Ghozali 2013 The purpose of heteroskidastity test is to test whether regression model occurred inequality variance residual
from one observation to another observation. A good regression model show there is no heteroscedasticity. Heteroscedasticty test use display
scatter plot the predicted value of dependent ZPRED with the residual SRESID
And
to test whether the variance of the residual homogeneous means heteroscedasticity.
c. Multicolinearity Test
The purpose of multicolinearity test is to found the if there any correlation between independent variable. We can see the test from the value
of tolerance and variance influence VIF factor. A good regression has VIF
around the number 1 one and have a number of Tolerance close to 1. If the
VIF value of less than 10 and the value of Tolerance T of more than 0.1 and less than or equal to 10, it means there is no multicolinearity but if the
value more than 10 and value of tolerance less than 0.1 it means there is multicolinearity.
d. Autocorrelation test
The purpose of autocorrelation test is to test whether in one regression has any correlation between the error in current period t with the
previous period t-1. A good regression model is regression that does not
45
have autocorrelation Ghozali,2013. The result of autocorrelation test will be based on Durbin Watson table.
1. if the result more than dU and less than 4-dU it mean there is no autocorrelation.
2. If the result less than Dl it‟s mean there is positive autocorrelation
3. If the result more than 4-dL it mean there is negative autocorrelation 4. If the result between dU and dL or between 4-dU and 4-dL it mean
cannot be concluded
3. Coefficient Determination
Coefficient Determination is statistical measurement of how
well regression line approximates the real data point. By knowing the valaue of
we can measure how far the ability of independent variablesROA, DAR, BOC can contribute towards dependent variable
GRI Indicator. There is range value in
from 0 to 1. If near to 0 most
of data variations cannot explained by regression model which mean the data is poor but if the value
approaches 1 it‟s means the data is great and independent variable can explain dependent variable.
4. Hypothesis Testing
The analysis method uses in this research is Multiple regression method. The researcher use multiple regression method because in this
research there are three independent variable and one dependent variable
46
which mean the researcher want to show when three variables are thought to be systematically connected by a linear relationship.
The regression is one of simplest tools in statistic and multiple regressions is a model with more than one independent variable. The
calculation of statistic can be significant if the value in critical points H0 rejected and if not it‟s mean its not significant H0 accepted. For testing
the hypothesis is used by model bellow :
Description : � �
a. Simultaneou Test F-test
Simultaneous test F-test used to find out the impact of overall independents variables ROA, DAR, BOC to dependent variables GRI
indicator. The level of significant is 5, the hypothesis of f test are : 1. If the significant F is more than 0.05 then Ha is rejected
2. If the significant F is less than 0.05 then Ha is accepted
47
b. Partial Regression Test T- test
The basic indicates of T-test is to examine the influence individuals of independent variable ROA, DAR, BOC to dependent
variable GRI Indicator. The value of t-test is compared with degree of believes
. The level of significance uses in this test is 5 or α 0.05 and the decision making is based on probability value :
1. If the significant T is more than 0.05 then Ha is rejected 2. If the significant T is less than 0.05 then Ha is accepted
E. Variable Operation
