C. Data Collection Method
Method use to collect data in this study is Field Research. Field research is a method to collect primary data. Primary data is a source of data that directly collect
from original source. Primary data is collected from mail-questionnaires, the questionnaires are given to competence parties, and in this case is external auditor.
Those parties or respondent is the most related parties to this study. Researcher also studied and examined the theory that build the variable and
theory that follow it. These can be done by reading and summarizing books, journal, article, and many others references.
D. Analyze Method
1. Descriptive Statistic This research is made by a descriptive statistic approaches. Descriptive
statistic is a statistic use to describe or analyze statistical evidence of the study by describing the data, but is not intent to make a larger assumption or generalized.
Sugiyono, 2005. Descriptive statistic is use to collect, process and analyze data, and also to explain the fact of audit plan that been studied, and being influenced
by the use of Control Self-assessment. 2. Data Quality And Normality Test
One of the weakness of mail survey is, respondent who willing to responses is they who had purpose to this study. Generally, there is a possibility
that the characteristic of the respondent may be different. This problem will be seriously if the response rate is very low. Researcher also tests the questionnaires,
using reliability and validity test. a. Reliability test
variable or construct. Questionnaires called reliable if the answer of the respondent is consistent or stable from time to time. Reliability measurement
can be done in One Shot Measurement. In these measurement we can use statistical test like Cronbach Alpha Test. Construct or variable is called reliable
if giving Cronbach Alpha value 0.60 Nunnally in Ghozali, 2005. b. Validity test
Validity test is used to test or measured validity of a questionnaires. Questionnaires called valid if the question can reveal what we want to
measures in the study. So validity test is intent to measures the question we made, are they really can measure what we want to measures.
c. Normality test Kurtosis is a measure of the extent to which observations cluster around a
central point, for a normal distribution, the value of the kurtosis statistic is 0. Positive kurtosis indicates that the observations cluster more and have longer
tails than those in the normal distribution and negative kurtosis indicates the observations cluster less and have shorter tails.
3. Hypothesis Test
The Paired-Samples Test procedure compares the means of two variables for a single group. It computes the differences between values of the two variables for
each case and tests whether the average differs or not. To perform t-test the step are:
a. Determines level of significance which will be applied in this research, the level is 5, or α = 0.05.
b. Deciding H
O
• Ho = Ha, Not Significant. Average value of both variables is identical
and no difference which is significant among both. •
Ha Ho, Significant. Average value of both variables is not identical and there is a difference which is signifying among both.
RESEARCH FINDINGS AND ANALYSIS A. Descriptive of Data
1. Descriptive Statistics
Before entering data analysis, first we have to know the object and sample of the study, the object of the study is Control Self-Assessment, being related to
the audit plan of external auditor, that’s why researcher decided to have external auditor as a research sample. The amount of external auditor in Jakarta based on
IAI 2006 directory book is 687, with tolerable error for 15, sample that are used in this research is 41 external auditors, for precaution researcher take 50
sample.
Table 4.1 Respondents of the study
No Position
Respondent Percentage
1 Manager
3 6
2 Partner
1 2
3 Supervisor
2 4
4 Senior
8 16
5 Expertise
2 4
6 Junior
34 68
50 100
Total
Table 4.1 explains about respondent, classified by their position as an external auditor. There are only three managers that are willing to respond, one
partner, two supervisor, eight senior, two expertise staff and thirty four junior auditors. From table we can see that there is a small response rate from middle
commonly to response, these kind of respondent is still relevant considering that junior auditor often sent to do the field work in client to collect audit data,
thereby junior interactively communicate with internal auditor, with a strict supervision.
Table 4.2 Auditor Experience
No Auditor Experience
Respondent Percentage
1 4 years audit experience
35 70
2 4 years audit experience
15 30
50 100
Total
Table 4.2 explains about auditor or respondents experience in audit. Most of the respondent or thirty five auditors had less than four years audit
experience. This was enough to fulfill the relevant criteria to become research object related to Control Self-Assessment, then there are fifteen respondents or
auditor who had more than four years experience in audit, these kind of respondent is the most relevant respondent, researcher categorized them as
middle up auditor.
Table 4.3 Descriptive Variables
50 47,00
82,00 3187,00
63,7400 6,73041
,537 ,662
50 24,00
52,00 1684,00
33,6800 6,57900
,031 ,662
50 audt_percep
csa_implement Valid N listwise
Statistic Statistic
Statistic Statistic
Statistic Statistic
Statistic Std. Error
N Minimum
Maximu Sum
Mean Std.
Kurtosis
Table 4.3 explains about respondent opinion valuescale when filling the questionnaires. From the table we can see that total sample is 50, and minimum
and CSA is 82 and 52. Sum of audit plan and CSA is 3187 and 1684. Average value or mean of auditor perception is 63,74 or 77, this means most of the
auditors assumed CSA is useful for audit primarly in audit planning, then for the implementation of CSA in companies, respondent gave an average value for
33,68 or 63 this means most of the auditors assumed CSA implementation in reality is not fully adopt and implement.
2. Data Quality and Normality test
This research use questionnaires to measures the variable. This kind of measurement need data quality and normality test to decided whether the data is
reliable, valid, and normal to be analyzed. a. Reliability Test
To decided whether the data is reliable or not, from the appendices 1, it shows that the data had N of cases = 50, and N of items = 23, with average
value of Cronbach Alpha 0.8543 for total item. With standard from Nunnaly 0.60, this mean the data is reliable because more than 0.60 or 0.85430.60,
therefore the reliability test is been passed through. b. Validity Test
To measures whether the questionnaires is valid or not, we can compare the value of r-count with r-table, the item of questionnaires is called valid if
the value of r-count r-table. The value of r-table or critical values of r- table is 0.3515, with degrees of freedom 23-2=22 and significant level at 5
or 0.05, for this study researcher also resulting the value that is near or almost equal with validity standard value, for those value researcher did not
excluded the result as long it still relevant to used. From the appendices 1,
not all the item of questionnaires is valid there is several items that didn’t through the validity test. There are 16 items that are valid and bigger than r-
table, which is y1, y2, y3, y4, y6, y7, y8, y9, y10, y11, y12, x3, x4, x5, x6, x7, x8, x9, and x10. Then beside the valid there also 7 items that are invalid,
the items is y5, x1, and x2. The invalid items will be excluded from the study. The invalid item is removed because they can’t explain or measures
the variable, that’s why they’re being discarded so there is no bias when analyzing the data.
c. Normality Test Table 4.3 above also describes about kurtosis. From table we can see
that auditor perception and CSA had positive value for 0,537 and 0,031. Data is called normally distributed if the value is 0, from the descriptive
table the value of auditor perception and CSA implementation is still normally distributed , if we see auditor perception is a bit oblique and for
CSA is normally distributed, but researcher still consider auditor perception is normally distributed, with this interpretation the data still can be called
normally distributed.
B. Analysis of Data 1.
Difference Test Analysis t-test with Paired Samples Test
The Paired-Samples Test procedure compares the means of two variables for a single group. It computes the differences between values of the two variables
for each case and tests whether the average differs or not.
Difference test t-test
1,10167 ,70279
,09939 ,90194
1,30140 11,084
49 ,000
audit_percep - csa_implemen
Pair 1 Mean
Std. Deviation
Std. Error Mean
Lower Upper
95 Confidence Interval of the Difference
Paired Differences t
df Sig.
2-tailed
Table 4.4 above, shows difference test t-test between both variables. From tables, t-test shows value t-calculate equal 11,084 while assessing t-table is
gotten by 2,0049 sees t-test table, means value of t-calculate is outside acceptance region Ho, herewith hence Ho refused and Ha is received, this
indicates that between both variables that is reality and hope happened a real difference, there is a gap between the use of CSA in auditor perception with the
implementation in companies. Then from value of sig two tailed in getting value 0000, with significant value equal to 5 or 0,005 and level of confidence level
equal to 95, hence this means level of difference between both variables hardly significant.
Chart 4.1 Area Acceptation Curve
Chart 4.1 shows the t-test in curve model, to test the hypothesis H
o
0 and H
o
=0, we used the t-calculate value and compare it with t-table value to know
Acceptation Area
Rejection Area
Rejection Area
2,0049 -2,0049
then the t-table value is 2,0049, which means the t- calculate value is out of the acceptation area, in this condition H
o
is rejected and there is a significant differences between reality and hope for the usefulness of CSA and its
implementation. To describe about the respondent answer, and in what section does CSA
very useful for audit plan and in what section does CSA really implemented by the companies, table 4.5 give a small view of it, without considering validity test.
Table 4.5 Respondent Answer in Percentage Value
1 Understanding of business and companies internal control
58,2 2
Risk Assessment 23,1
3 Others Audit objectives
18,7 1
Specific use of Control Self-Assessment 71,1
2 External auditor involvement in Control Self-Assessment process
21,1 3
Communication between organizations with their external auditor 7,9
CSA implementation in the companies CSA usefulness in audit plan
Table 4.5 description show that most of auditor haves a notion that CSA is most useful for understanding client business and internal control, 58,2, second
is for risk assessment 23,1, as for the implementation, most of the companies adopt CSA for Specific use, 71,1, this section include internal control review,
risk assessment, policy and procedure review, and training media for the employee. External auditor involvement and communication between them about
CSA is still low for about 21,1 and 7,9.
C. Discussion