Data Collection Method Analysis of Data 1.

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