EFFECT OF INTELLECTUAL CAPITAL DISCLOSURE ON STOCK PRICES

Changes and developments in technology and knowledge have an impact on the business world, making intangible assets critical to a company’s success. However, awareness about the importance of disclosure of intangible assets, especially intellectual capital, is still low. This study aims to analyze the disclosure of intellectual capital as measured using Value Added Intellectual Capital (VAIC) related to its relevance to stock prices as measured using the closing price. The population taken is companies that are listed on the Indonesia Stock Exchange, especially those in the infrastructure sector companies in 2020-2021. By using purposive sampling in the use of samples, it was found that there were 68 observations were acquired during the course of two-year observation period. The findings show that intellectual capital does not significantly affect the stock price variable. In other words, that more information about intellectual capital does not increase stock prices, and vice versa.


INTRODUCTION
Changes and developments in technology and knowledge have an impact on the business world.As a result, all companies need to make changes to the business strategy they use, namely from workforce-based to knowledge-based, in order to continue to survive.Therefore, intangible assets become very important for a company.Dutrianda & Pangaribuan (2020) states that "companies are highly dependent on the capacity to manage intangible assets in order to survive in the competition".Several studies have also concluded that there has been a decrease in the value relevance of accounting information as a result of an increase in unreported intangible assets (Simajuntak, 2022).
Referring to PSAK No. 19, an intangible asset is defined as an asset that cannot be directly converted into money because the disbursement process is very long (nonmonetary assets).The main characteristic of an intangible asset is that it can be recognized even without a physical form, a company that owns an intangible asset will potentially get future economic benefits from the asset, and the costs used to acquire the intangible asset can be calculated accurately.There are various components included in intangible assets, one of which is intellectual capital.Intellectual capital is not explicitly disclosed in PSAK (Kusufiyah et al., 2017), it's just stated that the use of intellectual property rights in a production process can reduce production costs in the future even though it does not increase current profits (Ikatan Akuntansi Indonesia, 2019).
In Indonesia, awareness of the importance of disclosing intellectual capital is still low (Nirmolo & Widjajanti, 2018).Companies also face challenges in treating and disclosing human resource costs, as well as calculating the benefits of investing in human capital (Harini et al., 2020).PSAK No. 19 does regulate intangible assets, but it does not explain how intellectual capital is measured and what elements in intellectual capital need to be disclosed (Fitriani, 2012).Costs related to the development of human resources are classified as expenses in conventional accounting, where these costs are written off annually in the financial statements and are not presented as assets in the balance sheet of financial statements.Meanwhile, according to Harini et al. (2020), "the cost of human resource development should be seen as an asset if the human resource development activity can produce benefits that can be enjoyed at present and in the future".
Further facts reveal that the laws governing limited liability companies (PT), especially Law Number 40 of 2007, Part IV, Article 66 which regulates the annual reports of PTs, do not oblige PTs to provide information about intellectual capital.Because of this voluntary nature, this intellectual capital information has a high probability of not being reported.This results in investors and other external parties not being able to ascertain how much potential the company's intellectual capital can provide added value (Dewan Perwakilan Rakyat Indonesia, 2007) Bruggen et al. (2009in Setianto & Purwanto, 2014) revealed that "there are at least four (4) things that can encourage companies to disclose intellectual capital, including: (1) disclosing intellectual capital makes companies have the ability to reduce financial statement asymmetry, (2) disclosing intellectual capital makes companies able to improve the relevance of financial reports, (3) disclosing intellectual capital can increase dedication and loyalty among employees and stakeholders, and (4) disclosing intellectual capital can provide a clear indication of how much real value and ability to create wealth in a company".
In Indonesia, there have been several studies examining the relevance of intellectual capital to stock prices.In research Dutrianda & Pangaribuan (2020), Suhermin (2014), andSunardi (2019) the findings show that "intellectual capital has a direct impact on stock prices, assuming the more intellectual capital, the higher the stock price".While in research conducted by Iskandar et al. (2019) the results show that "intellectual capital does not directly affect stock prices but will affect company performance which in turn affects stock prices".
Based on the phenomenon that has been described, the formulation of the problem raised is whether intellectual capital has a value relevance to stock prices?Therefore, this study seeks to test intellectual capital regarding its relevance to stock prices.The fundamental difference between the contribution of this research and the research conducted by Sugianto & Rudiawarni (2018) is where the research conducted by Sugianto & Rudiawarni (2018) focuses on human capital only with the variables used, namely the human capital disclosure index, the human capital disclosure index related to qualifications/competence, human capital disclosure index related to motivation/commitment, human capital disclosure index related to personnel.While this research focuses on intellectual capital as measured using VAIC.This research also has a novelty where in this research the object under study focuses on just one sector, namely companies that are in the infrastructure sector in 2020-2021.information disclosed by a company can be a signal for shareholders, prospective shareholders and other parties who have an interest in making decisions (Aida & Rahmawati, 2015).Information basically provides data, records, or descriptions regarding past, present, and future conditions related to the going concern of a company and the state of the securities market.High transparency regarding information is often considered a positive thing, but when costs and competitive opportunities are considered, independent supervisors will choose not to be too open about the information they have to the public (Pangaribuan, 2018).If the information presented is positive, it will certainly influence investors' investment decisions and will generate a positive opinion of the company which can result in an increase in stock prices.However, if the information presented has a negative value, it will also have an impact on the consideration of an investor to invest, giving rise to a negative opinion of the company and tend to result in a decrease in stock prices.
Disclosure of intellectual capital is believed to be able to provide a positive signal for investment decision makers.Where the higher the level of disclosure of intellectual capital, it will give a positive opinion, causing the stock price to rise.This is supported by the findings from the research by Dutrianda &Pangaribuan (2020), andSunardi (2019) which show that intellectual capital has a direct impact on stock prices, assuming the more intellectual capital, the higher the stock price.

RESEARCH METHODS
Quantitative methods and secondary data types were used in this study.Where the information collected comes from the financial reports of companies that are on the IDX list in the infrastructure sector for 2020-2021.
Companies that are included in the list of the Indonesian Stock Exchange, especially those in the infrastructure sector in 2020-2021 were the population of this study.This sector was chosen because according to Firer and Williams (2003) in Sugianto & Rudiawarni, 2018), "the service industry is an industry that is considered to have a high dependence on intellectual capital or is included in the High IC Intensive".
Purposive sampling was used in the sample selection process.This is because not all samples meet the criteria in this study.As such, with a total of two years of observation time, there were 68 observations that met the criteria to be a research sample.As for estimating the sample size in this study, the following requirements must be met: a) Companies that are included in the list of the Indonesia Stock Exchange, especially those in the infrastructure sector in 2020-2021 and publish financial reports that have been audited by auditors as of December 31 every year from 2020 to 2021, and during the year of observation are not excluded from IDX list.b) In its financial statements, it uses the rupiah as the reporting currency.c) The company's financial statements must contain the required variable components.In this study, stock prices are used as the dependent variable in this study, which is measured based on closing prices on December 30.While intellectual capital is assessed using the VAIC method formulated by Pulic (2000) as an independent variable and net income per share (NIS) which is calculated by dividing the amount of profit/loss attributable to the parent company with a weighted average shares outstanding as the control variable.
VAIC is a way to determine the ability of an entity to create added value, and is a measurement that describes the efficiency of value creation.Because the formulation of the calculation uses items that are listed and easy to find in the financial statements, the VAIC method is quite simple and easy to do.
The VAIC calculation formulation consists of 5 (five) stages: a) Calculation of Value Added (VA) Value added is a metric used to evaluate a company's success.Value added can be calculated using items that are listed and easy to find in the company's financial statements or from the reduction between the output which is the total revenue from sales and other sources with the input which is the cost of sales and other costs besides employee costs: VA = OUTPUT -INPUT Or you can also use the calculation of the addition of operating income (Operating Income/OP), employee costs (Employee Cost/EC), depreciation and amortization: VACA is a metric for calculating added value formed from physical capital.VACA can also be interpreted as the relationship between VA and capital employed which is influenced by human resources and structural capital.According to Ulum (2013) This study aims to examine intellectual capital assessed using the VAIC method regarding its relevance to stock prices, using earnings per share as a control variable.To test the hypothesis, it is performed using multiple regression analysis with the formula: Table 2 above presents some characteristics of the data.These characteristics include the mean, minimum and maximum of each variable tested in this study.
Table 2 shows the stock price which is the dependent variable having an average (mean) of IDR 1.008.600.Where the highest value in the sample is IDR 6.200.000,which is owned by PT Indosat Tbk. in 2021 and the lowest value is IDR 50.000 owned by PT Leyand Internasional Tbk. in 2020 and 2021 and PT Nusa Construction Enjiniring Tbk. in 2020.
The first independent variable, namely VAIC, has the lowest value -38.755 and the highest is 15.121 with an average value of 1.663.Based on observational data from 2020-2021, PT Tower Bersama Infrastructure Tbk has the highest VAIC score and PT First Media Tbk. has the lowest VAIC score.Then the second independent variable, namely NIS, has an average (mean) of 24.777 rupiah.Where the highest value in the sample is IDR 1.242.350,which is owned by PT Indosat Tbk. in 2021 and the lowest value is -799,000 owned by PT First Media Tbk.In a regression, a normality test is needed to determine whether the data regarding the variables in the regression, both dependent and independent, are normally distributed.A good regression model is a model composed of normally distributed data.For the normality test in this study using the One-Sample Kolmogorov-Smirnov test.Where if the result of Asymp.Sig.(2-tailed) is a value above 0.05 will conclude the data is normally distributed, and vice versa.

Normality test
Using the results of the One-Sample Kolmogorov-Smirnov normality test above, the resulting significance value is 0.156.Which means the data regarding the variables in this regression model are normally distributed because the results of the test are above 0.05.Hence, the next classical assumption test can be carried out.The significance values for VAIC and NIS in the Park test above were 0.309 and 0.614, respectively.Which means each variable has a significance value above 0.05.So that it can be said that the assumptions of the heteroscedasticity test are fulfilled, or there is no indication of heteroscedasticity in the study.Whether or not there is a relationship between independent variables in a regression model can be determined by conducting a multicollinearity test.A regression model will be said to be feasible if there is no relationship between one variable and another.By comparing the Tolerance and VIF values, it is possible to determine whether there is multicollinearity or not.If the Tolerance value is above 0.100 and VIF is below 10.000, it is concluded that there are no symptoms of multicollinearity.

Multicollinearity Test
The multicollinearity test results above show that each variable, both VAIC and NIS, has a Tolerance value above 0.10, namely 0.910 and VIF below 10.00, namely 1.099, which indicates that the assumption of multicollinearity has been fulfilled or there is no indication of multicollinearity.In the regression model, the autocorrelation test is used to determine whether there is a relationship between the residuals of one period and another.Where to determine whether autocorrelation exists in the regression model or not, the Durbin-Watson test can be used with the following assessment criteria: With a total of 68 observations and 2 independent variables, the dU obtained from the DW table is 1.563 (4 -dU = 2.437) and dL is 1.504 (4 -dL = 2.496).While the DW value is 1.833 as shown in the table.Thus, it can be concluded that dU < DW < (4 -dU) or there is no autocorrelation.How effective a regression model can explain the independent variable is evaluated using the coefficient of determination test, which is based on the R Square value.The NIS and VAIC variables contribute 47.1% to the stock price variable, according to table 7, where the Adjusted R Square value is 0.471.Meanwhile, 52.9% were influenced by factors outside the scope of this study.To ascertain whether the existing regression model in this study can be said to be fit (fit) and can be used to explain the independent effect on the dependent variable, it is necessary to have an F test.The F test will be fulfilled if the resulting significance level is lower than 0.05.

F Test
The value shown in the F test results table above is 0.000, which means the significance level is lower than 0.05.This shows that the existing regression model in this study can be said to be feasible and can be used to explain the effect of the independent variables on the dependent variable.To show how each independent variable affects the dependent variable individually it is necessary to do a t test.The significance value of each variable is used to determine the test results.If the significance value is below 0.05, it is concluded that the independent variable is said to affect the dependent variable.

T Test (Hypothesis Test)
In table 9, it is known that the VAIC variable has a significance value above 0.05, which is equal to 0.750.Thus, it is concluded that the intellectual capital variable has no influence on the stock price variable.This finding has the same conclusion as the findings of Iskandar et al. (2019) which shows that "intellectual capital does not directly affect stock prices but will affect company performance which will later affect stock prices".Assuming that if intellectual capital is managed optimally, then the company will have good working ability and that way it can attract many investors so that the company's shares will increase in value.However, these findings contradict the findings of Dutrianda & Pangaribuan (2020), Suhermin (2014), and Sunardi (2019) which show that "intellectual capital has a direct impact on stock prices, assuming the more intellectual capital, the higher the stock price".
Meanwhile the NIS variable has a lower result than 0.05, which is equal to 0.000.So, it is concluded that NIS, as a control variable, influences significantly and positively the stock price variable.These findings indicate that information regarding earnings per share has a significant impact on buying and selling of investors.This finding is in line with the findings of Sugianto & Rudiawarni (2018), where "NIS value has a significant influence on stock prices".Which means the more net profit per share, the higher the stock price.

CONCLUSION
This study aims to examine intellectual capital related to its relevance to stock prices.By using the VAIC method in measuring intellectual capital, the conclusions obtained indicate that intellectual capital does not directly affect the stock price variable.Which means that the disclosure of intellectual capital does not make stock prices rise or fall.
Meanwhile, this study has limitations in which that the observations used are too few and the data used only uses secondary data.Therefore, for further research it is suggested that a different method be used to measure intellectual capital and that additional samples or observations be used to obtain better findings.In addition, data can also use data that includes secondary data and primary data obtained through direct observation of the company.

Table 1 . Research Sample
, one unit of capital used can create a high rate of return, which allows the company to be superior in terms of capital employed.VACA can be calculated by dividing the company's added value by the company's existing funds (such as equity and net income): Calculation of Value Added Human Capital (VAHU) VAHU refers to the amount of added value that can be obtained with costs associated with human resources.This figure illustrates how big the contribution per one rupiah of costs obtained from investing in human capital is to the company's added value.VAHU is calculated by dividing value added by employee costs: CURRENT ADVANCED RESEARCH ON SHARIA FINANCE AND ECONOMIC WORLDWIDE | CASHFLOW https://ojs.transpublika.com/index.php/CASHFLOW/E-ISSN : 2809-8226 | P-ISSN : 2809-848X 353 c)

Table 4 . Heteroscedasticity Test Result
The heteroscedasticity test is a test that determines whether the variance of the residuals does not have the same across all observations in the regression model.The Park test was chosen for the heteroscedasticity test, where this test method is by looking at the CURRENT ADVANCED RESEARCH ON SHARIA FINANCE AND ECONOMIC WORLDWIDE | CASHFLOW https://ojs.transpublika.com/index.php/CASHFLOW/E-ISSN : 2809-8226 | P-ISSN :

2809-848X 355 significance
value of the test results.Research does not have signs of heteroscedasticity if the significance results show more than 0.05, and vice versa.