Administration and Optimization of Fixed Assets at the Secretariat of Election Commission for West Java Province, Indonesia

State property is the object of administration, consisting of current assets (inventory), fixed assets (land, equipment and machinery, buildings, roads, irrigation, and networks, other fixed assets and construction in progress); as well as intangible assets (partnership assets with third parties, intangible assets, fixed assets discontinued from use). The administration of state property is a continuous process in order to optimize the use of state property. Sadly, it was found that the realization of the administration and management of state property, especially fixed assets have not run optimally. This is supported by the findings of Audit Board of the Republic of Indonesia (BPK) on fixed assets, whose value of findings increased, which was originally Rp. 4.4 trillion in 2015, to Rp. 10 trillion in 2016.

According to Tulungen (2014), the administration of state property is the activity of BMN starting from asset management, registration, classification, reporting in stages to BMN and follow up on the findings of state property management. Febrianti (2016) revealed that bookkeeping, inventory, and reporting are simultaneously have positive and significant effect on the quality of financial statements in the Local Government of Kubu Raya Regency, Indonesia. This can be seen through the presentation of bookkeeping and recording of regional goods in the inventory card list which the accessibility for users of goods that also affect the quality of financial statements. Nasution et al. (2015), stated that the implementation of health equipment optimization activities at the Mental Hospital of North Sumatra Province, Indonesia is not in accordance with the applicable Standard Operating Procedures in the hospital. It is expected that the improvement of administrative system (documentation and archive) and optimization activities of health equipment and supporting equipment could improve the effectiveness and optimization of laboratory equipment and supporting equipment.

The Secretariat of General Election Commission for West Java Province also conducts the administration and management of the state property in accordance with the prevailing regulations, but the administration and management of the state property carried out, in particular, fixed assets, is improperly implemented. This are due to limited human resources in terms of goods management, especially in the operation Management Information System and Accounting of State Property (SIMAK BMN), and limitations in stock operations. Lack of socialization and guidance from relevant agencies regarding the rules of reports preparation for goods or financial reports that are often experiencing the latest updates.

This study is conducted to determine the problem of administration and optimization of fixed assets in the Secretariat of Election Commission for West Java Province. Previous research revealed several problems such as recording and reporting of fixed assets that have not been done accordingly, asset management did not comply with the standard, where fixed assets have not been optimally utilized, and the existence of assets that have not been known its existence. In the General Election Commission, research on the administration of state property is still lacking, as revealed by Tulungen (2014), which states that research on the management of state property in KPU in North Sulawesi is still very rare. Therefore, the purpose of this study is to determine the effect of administration (bookkeeping, inventory, and reporting) on the optimization of fixed assets in the Secretariat of the General Election Commission for West Java Province.

The purpose of data collection is to understand social phenomena which are associative, using quantitative method (Sugiono, 2013). The sample of this study is selected using purposive sampling, where respondents are all State Civil Employees (ASN) at the Secretariat of Election Commission for West Java Province, which amounted to 38 employees. The hypothesis is analyzed using multiple regression analysis, having previously tested the reliability and validity of research instruments, and the classical assumptions, before performing statistical test on the hypothesis. Before distributing the questionnaires to the respondents, a pilot test was conducted to determine the reliability and validity of the questionnaire.

The implementation of asset management activities is divided into two main activities, namely administration and application recording, and physical implementation. The implementation of system or application recording in Management Information System and Accounting of State Property (SIMAK BMN). The physical execution involves the implementation of the stock of current assets and fixed assets. The stock for this hospital is done twice a year. The fixed asset data according to Goods and Financial Statement for the period of 2014 to 2017 are as follow:

The result of the pilot test showed that items in bookkeeping, inventory, reporting, and optimization result with Pearson correlation > 0.3. Therefore, it can be concluded that all items in bookkeeping, inventory, reporting, and optimization are valid. Through the reliability test, the following results are obtained and can be seen in Table 3.

Based on the above table, all items have been declared as valid and reliable. The criterion of reliability criteria is 0.7 All of these variables meet the criteria with Cronbach's Alpha greater or equal to 0.70. The results from the 38 respondents are as follows:

The table shows that bookkeeping, inventory, reporting and optimization items show valid results with criteria that is Pearson Correlation> 0.3. It can be concluded that all items in bookkeeping, inventory, reporting, and optimization is valid. The reliability test results can be seen in Table 5.

Based on Table 5, all items that have been declared valid also declared reliable, because Cronbach's Alpha is greater than 0.70. The classical assumption test is the requirement that must be met in the linear regression model so that the regression model can be used as a model to test a hypothesis (Hidayat, 2017) using normality test, outliers, multicollinearity, and heteroscedasticity (Ghozali, 2016). The normality test aims to test whether, in the regression model, the intruder or residual variable has a normal distribution (Ghozali, 2016) using One-Sample Kolmogorov-Smirnov test. The result can be seen in Table 6.

The result from the normality test that is asymp sig value equal to 0,074. This value is smaller than the level of significance used that is 0.10 (10%). Based on the normality test criteria, it can be concluded that the data is not normally distributed, so it is necessary to test outliers to dispose of data that deviate so that data can be distributed normally. In this study, it is likely that the outliers that arise are from the population we take as samples but are not normally distributed due to their extreme value. After testing outliers then re-test the normality to determine whether the data has been distributed normally or not. In testing outliers, using case wise diagnostics, to analyze data that has a false classification of the results of observations made by respondents, thus causing data not normally distributed. The outliers test result can be seen in Table 7.

From the test, data affected by outliers are case number 3 and 4, questions number 3 and 4 in the questionnaire answered by respondents. Based on the analysis of case wise diagnostic, data affected by the outliers must be discarded, thus 2 questionnaires were removed from 38 questionnaires collected from the respondents. Furthermore, the normality test again, for 36 data questionnaires, and obtained results as in Table 8.

The result of normality test in Table 8 shows that the value of asymp sig obtained is 0.364. This value is greater than the level of significance used is 0.364> 0.10. Based on the normality test criteria, it can be concluded that the data is normally distributed, so the research can proceed.

Multicollinearity test was conducted to test the correlation between independent variables in the regression model used. Table 9 shows that he multicollinearity value can be detected with Tolerance ≤ 0.10 and Variance Inflation Factor (VIF) ≥ 10 (Ghozali, 2016). Here are the results of multicollinearity testing:

Table 9 shows that bookkeeping, inventory and reporting have a tolerance value greater than 0.1 (Tolerance ≤ 0.10) that is 0.416; 0.495; 0,584 and VIF value less than 10 (Variance Inflation Factor (VIF) ≥ 10) that is 2,405; 2.021; 1,711, so it can be concluded that there is no multicollinearity in the regression model.

Heteroskedasticity test was conducted to find out whether there is a variance or diversity from residual one observation to another observation (Ghozali, 2016). If there is no regular pattern, that all points spread above (+) and below (-) Y-axis, then the regression model does not occur heteroscedasticity. The result of heteroscedasticity can be seen in Figure 1.

Figure 1 shows spots spread above (+) and below (-) Y axis, so it can be concluded that there is no heteroscedasticity in the regression model, so the regression model is feasible to use. In this study, the multiple regression methods are used to determine the effect of independent variables (independent variable) that is Bookkeeping, Inventory and Reporting to the dependent variable (Optimization). The following results of the regression equation in this study:

Based on Linear Regression Result, the Multiple Regression model in this study becomes:

Y = 4,301 + 0,208 X1 + 0,346 X2 + 0,580 X3 + e; or

Optimization = 4.301 + 0.208 Bookkeeping + 0.346 Inventory + 0.580 Reporting + e

which means:

i. a = 4.301 means if the value of Bookkeeping, Inventory and Reporting is equal to zero, then Optimization equals 4.301.

ii. ß₁ = 0.208 means if the Bookkeeping variable increases, then Optimization increases by 0.208.

iii. ß₂ = 0.346 means if the Inventory variable increases, then Optimization increases by 0.346.

iv. ß₃ = 0,580 means if the Reporting variables increase, then Optimization increases by 0,580.

v. Y = Optimization

vi. X₁ = Bookkeeping

vii. X₂ = Inventory

viii. X₃ = Reporting

ix. e = error

To find out whether know the influence of each independent variable has specific influence on the dependent variable, a t-test (Ghozali, 2016) was carried out. The hypotheses tested are:

H₀₁: ß₁ = 0, Bookkeeping Fixed Assets (X₁) has no effect on Fixed Assets Optimization (Y).

H_A1: ß₁ ≠ 0, Bookkeeping Fixed Asset (X₁) affects Fixed Assets Optimization (Y).

H₀₂: ß₂= 0, Inventory Fixed Assets (X₂) has no effect on Fixed Assets Optimization (Y).

H_A2: ß₂ ≠ 0, Inventory Fixed Assets (X₂) affects Fixed Assets Optimization (Y).

H₀₃: ß₃ = 0, Reporting Fixed Assets (X₃) has no effect on Fixed Asset Optimization (Y).

H_A3: ß₃ ≠ 0, Reporting Fixed Assets (X₃) affects Fixed Assets Optimization (Y).

Based on the statistical tests conducted using α = 10%, it can be concluded that: (1) bookkeeping has a Sig value of 0.236 greater than 0.10, meaning H01 is accepted. It was concluded that bookkeeping had no significant effect on optimization; (2) inventory has a Sig value of 0.055 is smaller than 0.10, meaning H02 is rejected. It is concluded that inventory has a significant effect on optimization; and (3) reporting has Sig value of 0.022 is smaller than 0.10, meaning H03 is rejected. It is concluded that reporting has a significant effect on optimization.

Based on the results of partial influence analysis, inventory and reporting have an influence on optimization, the magnitude of the influence of inventory and reporting against optimization through the coefficient of determination:

Based on Table 12, the value of r for inventory with optimization is 0.660, and calculated based on the formula coefficient of determination, where D = r2 x 100%, obtained results (0.660) 2 x 100% is 43.56%. Thus, it can be concluded that the effect of inventory to optimization is 43.56%. Reporting with optimization has an R-value of 0.662 so the result (0.662) 2 x 100% is 43.82%, then the effect of reporting on optimization is 43.82%.

The F statistic test is used to test the overall significance of the independent variables whether simultaneously or simultaneously or together and significantly affect the dependent variable (Ghozali, 2016). Using significance (α) 10%, simultaneous hypothesis testing results bookkeeping, inventory, and reporting on optimization can be seen in Table 13.

In Table 13, the Sig value obtained is 0.000. This value is smaller than the level of significance used that is 0.10. It is concluded that the result of F test in the regression analysis is significant, which means simultaneously or simultaneously bookkeeping, inventory and reporting effect on optimization.

The Coefficient of Determination (R2) is a coefficient value that can be used to predict the contribution of the influence of independent variables to the dependent variable. A Coefficient of Determination can be used if the F test results in multiple regression analysis are significant (Raharjo, 2017), with the result:

In Table 14, the result of F test is significant, so the Coefficient of Determination (R2) produced can be used to predict the contribution of independent variable influence to the dependent variable. Adjusted R Square value of 0,550 or 55%, this indicates that the influence of simultaneously bookkeeping, inventory and reporting to optimization of 55% while the remaining 45% influenced by other factors not examined in this study.

From the tests that has been conducted, the result shows that bookkeeping has an insignificant effect on optimization of fixed asset in Secretariat of Election Commission for West Java Province. The result of this research has similarity with result of research of Tumarar et al (2015) that mentioned the administration has done according to Regulation of Minister of Home Affairs Number 17 the Year 2007 as technical guidance in the management of local property, but the utilization of the goods still not optimal because not all utilization activity is done. Although the administration, which one of the elements is Bookkeeping already done according to existing guidelines, if the utilization is not maximized, then Optimization has not been achieved. The results of this study answered the hypothesis that bookkeeping (fixed assets) affect the optimization of fixed assets in the Secretariat of Commission Election for West Java Province but not significant.

The test also shows that the inventory significant effect on the optimization of fixed assets in the Secretariat of Election Commission for West Java Province. Suciyani (3013) explains that optimization of idle asset utilization in Bandung Square area can be implemented after identifying and analyzing asset potential and conducting asset feasibility test, in the opinion of Siregar (2004) that asset management optimization maximizes asset availability and asset utilization, while minimize the cost of ownership. It also addresses the problems in the Secretariat of Commission Election for West Java regarding the limitations in carrying out the stock of hospitalization and inventory. The results of this study answer the hypothesis that the Inventory Optimization assets remain influential on the Secretariat of Election Commission for West Java Provincial, significantly.

For reporting variables, the test shows that reporting has significant effect on the optimization of fixed assets in the Secretariat of Election Commission for West Java Province. This result is supported by Hendrikus S.B (2009), that more comprehensive management information system implemented in asset management, the more effective asset management, and ease in obtaining accurate and accurate asset information. The results of this test also answer the problems that become obstacles in the preparation of State Property (BMN), namely the limited personnel in terms of management of goods, especially in operating Management Information System and Accounting for state property application. These results indicate that the presence of personnel with the right amount, understand and master the use of Management Information System and Accounting for State Property(SIMAK BMN) application for the preparation of reports, as well as the ease of information and development (update) applications that are easy to learn and use, is expected to generate reports State Property which contains data and information fixed assets in the Secretariat of the General Election Commission of West Java Province. Accurate State Assets reports will make asset management more effective. The results of this study answer the hypothesis that Reporting affects the optimization of fixed assets in the Secretariat of Election Commission for West Java Province, significantly.

Through simultaneous testing, bookkeeping, inventory, and reporting affect the optimization of fixed assets. This is supported by Febrianti (2016) which revealed that bookkeeping, inventory and reporting simultaneously have positive and significant effect on the quality of financial report in Local Government of Kubu Raya Regency, due to the presentation of bookkeeping and recording of Properties of the Right Area in Inventory and Inventory Card list, providing easy access for users of goods that also affect the level of quality of financial statements. According to Tulungen (2014), administration of state property is the active activity of State Property’s asset management, registration, classification, reporting in stages to BMN and follow up on a finding of BMN management.

The results of this test are also supported by previous research, to answer the hypotheses that have been determined at the beginning, that the administration activities (Bookkeeping, Inventory, and Reporting) affect the Optimization of fixed assets in the Secretariat of Election Commission for West Java Province.

In conclusion, inventory significantly influence the optimization of fixed assets in the Secretariat of Election Commission for West Java Province by 43.56%. The reporting of fixed assets also significantly affects the optimization of fixed assets in the Secretariat of Election Commission for West Java Province by 43.82%. Meanwhile, bookkeeping has no significant effect on the optimization of fixed assets in the Secretariat of the General Election Commission of West Java Province. However, bookkeeping variable, inventory, and reporting of the fixed asset have significant effect to optimization of fixed asset in Secretariat of Election Commission for West Java Province by 55% while the rest 45% influenced by other factors not examined in this study.

Suggestions that can be given in this study by intensifying the implementation of inventory of fixed assets and inventory result can be taken into consideration for procurement, repair, transfer, even asset deletion. Increase the number of personnel performing periodic Inventory of assets in each room that will provide periodic Reporting to the responsible or State Property Administrations, renewing Inventory Cards of Goods contained in each room, so that the goods data is equal to the total and quantity of goods in that location. People whose operating Management Information System and Accounting for State Property Application (SIMAK BMN) always follow the application update and understand how to operate optimally. The various limitations that can affect the results of the study such as limited number of respondents, so this study recommend for the next research to expand the scope of the research in order to obtain larger number of respondents and observations so that the results obtained more statistically specific, for example by doing research throughout the Secretariat Election Commission for Regency or City in West Java General, about 27 Secretariats.