The Illomata International Journal of Management Ilomata International Journal of Tax & Accounting P-ISSN: 2714-9838; E-ISSN: 2714-9846 Volume 3, Issue 4 October 2022 Page No. 397-407 397| Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc Biological Asset Disclosure in Indonesia Aminah 1 , Djoko Suhardjanto 2 , Rahmawati 3 , Jaka Winarna 4 , Dea Oktaviana 5 15 University of Bandar Lampung, Indonesia 234 Sebelas Maret University Surakarta, Central Java Indonesia Correspondent: aminah@ubl.ac.id 1 Received : July 30, 2022 Accepted : October 10, 2022 Published : October 31, 2022 Citation: Aminah., Suhardjanto, D., Rahmawati, Winarna, J., Oktaviana, D.(2022). Biological Asset Disclosure in Indonesia. Ilomata International Journal of Tax and Accounting, 3(4), 397-407 https://doi.org/10.52728/ijtc.v4i1.434 ABSTRACT: The development of companies in the agricultural sector is supported by the availability of information, which is also a consideration for decision- making by company owners or company management. As a result, the company's annual report must include as much information as possible. Agricultural companies are required to disclose their biological assets under PSAK 69. However, many agricultural companies have not fully disclosed their biological assets. The focus of the research is to observe how biological assets, company growth, auditor type, and public ownership influence biological assets disclosure. Plantation & crops companies listed on the Indonesia Stock Exchange (IDX) are the population for this study, with a total of 25 entities. 13 out of 25 companies became the research sample taken using a purposive sampling method. The research technique uses panel data regression in Eviews 10. The findings of this study are biological assets intensity and auditor type have a significant positive impact on biological assets disclosure. Company growth has an insignificant positive effect on the disclosure of biological assets, public ownership has an insignificant negative effect on the disclosure of biological assets. Keywords: Biological assets; Auditor type; Growth; Public Ownership; PSAK 69. This is an open access article under the CC-BY 4.0 license. INTRODUCTION The agricultural sector is one of the foundations of national economic growth. it is increasingly important and strategic, marked by an increasing contribution to GDP (Khairiyakh et al., 2016; Nasrun et al., 2020; Widada et al., 2020). Based on data from Agricultural Indicators 2020, the agricultural sector contributed 13.70% to the total Gross Domestic Product (GDP), an increase of 0.99% from the previous year. Agricultural companies (plantation) are a combination of labor, land, and animals, which play a role in increasing agricultural productivity as a source of income, comply food and industry demand, encouraging exports, and providing wide employment opportunities (Arham et al., 2020; Bashir et al., 2019; Bohušová & Svoboda, 2016). The availability of information must be fully contained in the company's annual report to support the company's growth in the agricultural sector (Arvidsson, 2011; D. Kurniawati & Yuliando, 2015; Velasco-Muñoz et al., 2021). Financial reports that provide relevant and extensive information mailto:aminah@ubl.ac.id https://doi.org/10.52728/ijtc.v4i1.434 Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 398 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc about financial status, investment prospects, company value, and risks can help companies become more transparent (Mansoor, 2021; Martini, 2012; Prekazi, 2022). PSAK 69 was approved by DSAK IAI on 16 December 2015 and adopted from International Accounting Standard (IAS) 41 for Agriculture, which was implemented on 1 January 2018. PSAK 69 requires companies to disclose their biological assets. Biological assets consist of a group of biological assets, agricultural activities, as well as gains and losses from biological assets during the period (Bozzolan et al., 2016; Herbohn & Herbohn, 2006; H. Kurniawati, 2013). The entity also discloses the difference between the fair value and cost of selling agricultural products in the current period, the location and amount of recorded biological assets, also biological asset adjustments. The transformation accounting treatment of biological assets using the fair value method has become a controversy where according to PSAK 69, the historical cost method does not reveal the true value in the financial statements because biological assets are recorded at the costs incurred. Fair value transformation will result in various valuation methods, and reduce the quality of comparability of financial statements (Elad & Herbohn, 2011; Gonçalves & Lopes, 2014; Octisari, 2020). Several countries that have implemented IAS 41 agriculture have difficulty in measuring the fair value of some biological assets, so it isn’t worth the benefits received (Dewi et al., 2018). After examining the annual reports of several agricultural companies listed on the Indonesia Stock Exchange in 2018-2020, many agricultural companies haven’t fully disclosed their biological assets . Companies only disclose 38.68% of their biological assets (Hayati & Serly, 2020). In other study the disclosure index of biological assets in Bangladesh is still very low with an average of 29.30% (Mirović et al., 2019) LITERATURE REVIEW Agency theory is an arrangement of one or more people (principals) to involve other people (agents) in doing some work on their behalf and empowering agents to make some decisions (Jensen & Meckling, 1976). Business owners need the information to evaluate their business as a fundamental for decision making, while company management provides good information to principals that can add value to the company later (Buchanan et al., 2018). This problem creates a condition of information imbalance or often called information asymmetry, thus requiring control over the company. One of them is agents must disclose information so that business owners can analyze and evaluate management's performance in managing the investments allocated to them as effectively as possible (Healy & Palepu, 2001). Agency theory claims that disclosure can be considered as a procedure to control the performance of managers, meaning that disclosure is the right method to monitor the performance of agents and the credibility of the company can be increased in the eyes of shareholders (Mirović et al., 2019). The intensity of biological assets is defined as the proportion of investment which can show the amount of money the entity invests in its biological assets (Alfiani & Rahmawati, 2019; Carolina et al., 2020) Total assets that have changed, either increasing or decreasing also reflect the company's growth (Brigham & Houston, 2014; Cindy & Madya, 2018). Auditing can bridge the presentation of the company's financial statements where conflicts of concern often occur. To avoid information asymmetry and biased financial statements, the report must be checked by an independent auditor so the financial statements can be used by shareholders (Lubis & Dewi, Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 399 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc 2020). The percentage of total share ownership of the general public which is not a large institution and has no special relationship with the company is called public ownership. METHOD The object of this research is plantation & crops companies listed on the Indonesia Stock Exchange from 2018 to 2020 with a population of 25 companies. The purposive sampling method was used in the selection of samples and obtained a sample of 13 companies. The type of data in this study is quantitative data with the panel data type. Documentation techniques are used for data collection by collecting annual reports of plantation & crops sub-industry companies listed on the Indonesia Stock Exchange (IDX) from 2018 to 2020 which are accessed through www.idx.co.id or the company's official website. The total data to be observed in this study is 13x3=39 observation data. To facilitate the variable comprehension used in the research, descriptive statistical tests were conducted to define the data by knowing the mean, median, standard deviation, minimum and maximum value of the observed data for each variable (Ghozali, 2013). The research uses panel data regression analysis techniques with 3 approaches, namely the estimates of the common effect model (OLS), the fixed effect model (LSDV), and the random effect model (GLS). The panel data regression model was selected using three tests, namely the Chow test (F-test), the Housman test, and the Lagrange Multiplier (LM) test. Then, the hypothesis test consists of the coefficient of determination test (R-squared), the F statistic test, and the t statistic test (partial). Below are the variables used in the research provided in table 1. Table 1. Operational Definition and Measurement variables Research Variable Operational definition Object measurement Biological Asset Disclosure (Y) Measured using a dummy variable. If the entity discloses each item in the financial statements, it is assigned 1, while if it does not disclose items, it is assigned 0. Biological Asset Intensity (X1) Determined by comparing the company's biological assets with the company's total assets (Carolina et al., 2020). Company growth (X2) Dividing the total assets of the current period minus the total assets of the previous period by the number of assets of the previous period (Alfiani & Rahmawati, 2019) ( ) ( ) ( ) Auditor Type (X3) Measurement of the auditor The following is the Big-Four KAP Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 400 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc type uses a dummy variable. If the entity is examined by KAP Big-Four, it is given a score of 1. Then, if the entity is examined by KAP not Big-Four, it is given a score of 0. proposed by the Directorate of IAPI in 2010: 1. Ernst & Young, in alliance with KAP Purwantono, Suherman & Surja; 2. Delloite Touche Tohmatsu, in alliance with KAP Satrio Bing Eny & Partners; 3. KPMG (Klynveld Peat Marwick Goerdeler), in alliance with KAP Siddharta Widjaja & Partners; and 4. PWC (PricewaterhouseCoopers), in alliance with KAP Tanudiredja, Wibisana, Rintis & Partners. Public Ownership (X4) Public ownership is the sum of all public shareholdings divided by the number of company shares (Azzahra et al., 2020). RESULT AND DISCUSSION Descriptive Statistic Analysis Table 2. Descriptive Statistic Analysis Result BAD BAI CG AT PO Mean 0.541234 0.013777 0.034423 0.564103 0.244526 Median 0.540541 0.013679 0.023844 1.000000 0.237312 Maximum 0.702703 0.030819 0.735217 1.000000 0.457119 Minimum 0.378378 0.001828 -0.371432 0.000000 0.016072 Std. Dev. 0.081669 0.007295 0.181611 0.502356 0.128091 Source: Eviews 10 processed data, 2022 Table 2 reveals the mean value of disclosure of biological assets (BAD) of 0.54. The standard deviation of the biological asset disclosure (BAD) is 0.081. The minimum value of BAD is 0.38 while the maximum value of BAD is 0.70. The mean value of biological asset intensity (BAI) is 0.014. The standard deviation score of the biological asset intensity (BAI) is 0.007. The minimum value of BAI is 0.002 and the maximum value of BAI is 0.031. The mean value of company growth (CG) is 0.034. The standard deviation value of company growth (CG) is 0.182. The minimum value for company growth (CG) is -0.371 and the maximum value for company growth (CG) is 0.735. The mean value of auditor type (AT) is 0.564. The value of the auditor type standard deviation (AT) is 0.502. The minimum value for auditor type (AT) is 0.000 and the maximum value for auditor type (AT) is 1,000. Panel Data Regression Model Selection For the selection of this research model, the authors conducted the Chow test and Housman test. The Chow test was run to find out which of the Common Effect Model (CEM) and Fixed Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 401 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc Effect Model (FEM) models were more optimally used. While the Housman test is used to ensure a suitable model between the Fixed Effect Model (FEM) and the Random Effect Model (REM). Table 3. Recapitulation of model selection test results Uji Chow Nilai Probabilitas F 0,0020 Uji Hausman Nilai Probabilitas Chi Squares 0.5704 Source: Processed data, 2022 From the results of the above recapitulation, in the Chow test, it is known that if the prob-F value of 0.0020 is declared less than the significant level (0,002 < 0,05) then the more appropriate model between the two is the Fixed Effect Model (FEM). Furthermore, based on the results of the Hausman test above, it shows that the probability value chi-squaresres is greater than the significant level (0,5704 > 0,05). It can be concluded that the Random Effect (REM) model is more suitable than the Fixed Effect (FEM) model. The Lagrange multiplier test was not carried out in this study because this test was used to compare CEM and REM, while in the Chow test, FEM was more precise than CEM, and REM was better used than FEM. Therefore, the Random Effect (REM) model was chosen to analyze the variables in this research. The following is the equation of the Random Effect (REM) model. BADit = 0 + 1 + 1BAI1it + 2CG2it + 3AT3it + 4PO4it + eit BAD : Biological Asset Disclosure 0 : Unknown parameter indicating the average of the population intercept BAI : Biological Asset Intensity CG : Company growth AT : Auditor Type PO : Public Ownership µ : It is random which explains the differences in the behavior of individual companies Classic Assumption Test Gujarati & Porter (2009) stated that the equation using the Generalized Least Squares (GLS) approach has passed the classical assumption. The panel data regression model which is the GLS is a random effect (REM) model, while the common effects (CEM) and Fixed Effect (FEM) models use ordinary least squares (OLS), so they must pass the classical assumption test and reach BLUE (Best Linear Unbiased Estimator). Because the regression equation in this study uses a random effect model where the Generalized Least Squares (GLS) estimation method is said to be able to overcome heteroscedasticity and autocorrelation, it is not necessary to test the classical assumptions. In this study, the authors only tested the normality of the distributed data, namely the normality test and found out whether there was a correlation between the independent variables, namely the multicorniality test. Normality test The jarque-Berra method was used in testing the normality of this study. The results obtained are as follows. Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 402 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc Picture 1. Normality Test Diagram It can be seen that the jarque-berra probability value is 0.866061 greater than the significance level (0.87 > 0.05), so the research data in this research model has a normal distribution. Multicollinearity Test Paired-correlation method was used to test the multicollinearity of the independent variables in this study. The results of the multicollinearity test are as follows. Table 4. Multicollinearity Test Results BAI CG AT PO BAI 1.000000 -0.216952 0.221788 0.075464 CG -0.216952 1.000000 0.184942 0.049618 AT 0.221788 0.184942 1.000000 0.584951 PO 0.075464 0.049618 0.584951 1.000000 Source: Processed data, 2022 Because the table above shows that the correlation value for all independent variables is less than 0.85, it can be concluded that there are no signs of multicollinearity in each of the independent variables of this study. Coefficient of Determination Test (R-Squared) The Coefficient of Determination Test (R-squared) is used to find out how well the model can explain the dependent variable. It is known that the Adjusted R-squared value of 0,200402 which shows the percentage of the variable intensity of biological assets, company growth, type of auditor, and public ownership in explaining the disclosure of biological assets is 20.04%, with the remaining 79.96% being the proportion of other factors that influence the dependent variable. F-Statistic Test The F statistical test was carried out to determine whether the model used in the research was feasible by seeing whether the dependent variable was usually explained by all the independent variables together. Table 4. Recapitulation of F-statistic Test Results Description Value F-statistic 3.380977 Prob(F-Stat) 0.019673 Source: Processed data, 2022 Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 403 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc Table 5 shows the F-statistic value of 3.380977 where the F-Calculate is greater than the F-table (3.38 > 2.65) and the prob F-statistic value of 0.019673 is smaller than the significance level (0.01< 0.05) which means that the variables of biological asset intensity, company growth, auditor type, and public ownership together can explain the variable of biological asset disclosure, so it can be concluded that the Random Effect model is feasible for this research. t-Statistic Test (Partial) Table 5. t-test Results Following are the conclusions from the table above. 1. Hypothesis testing 1 The t-statistic test obtained a coefficient value of BAI 3.414 and the prob-value was lower than the significant level (0.03 <0.05), so it was concluded that the intensity of biological assets had a positive and significant effect on the disclosure of biological assets. 2. Hypothesis testing 2 The coefficient value of the CG variable is 0.006382 and the probability score is higher than the significant level (0.82 > 0.05), which means that the company's growth has a positive and insignificant effect on the disclosure of biological assets. 3. Hypothesis testing 3 The AT coefficient value is 0.083176 and the prob-value lower than the significant level (0.02 < 0.05), so it can be stated that the type of auditor has a positive and significant effect on the disclosure of biological assets. 4. Hypothesis testing 4 The coefficient value of the PO is -0.162294 and the probability value is higher than the significant level (0.26 <0.05), which means that public ownership has a negative and insignificant effect on the disclosure of biological assets. Effect of Biological Asset Intensity on Biological Asset Disclosure The results showed that biological asset intensity had a positive and significant effect on the disclosure of biological assets. This result is in line with agency theory. Agricultural companies place biological assets as the main assets so the size of biological assets in financial statements has an impact on company owners in making decisions according to agency theory (Carolina et al., 2020). With the increasing value of biological assets, there is a tendency for companies to disclose more information about biological assets to convey more transparent information, so company owners know the condition of their biological assets, so that owners can evaluate the company's potential and determine business strategies that must be improved in the future. It concurs with the research of Hayati & Serly (2020), Gonçalves & Lopes (2014), Azzahra et al. (2020), Carolina et al. (2020), Zulaecha et al. (2021) which concludes that the intensity of Variabel Koefisien t-statistik Prob. C 0.486751 12.05483 0.0000 BAI 3.413585 1.928609 0.0322 CG 0.006382 0.138026 0.8910 AT 0.083176 2.445722 0.0198 PO -0.162294 -1.140625 0.2620 Source: Processed data, 2022 Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 404 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc biological assets has a positive and significant effect on the disclosure of biological assets. However, this study contradicts the research of (Alfiani & Rahmawati, 2019; Mirović et al., 2019) which state that the intensity of biological assets has a negative effect on the disclosure of biological assets. The Effect of Company Growth on Disclosure of Biological Assets The company growth shown by the research results has a positive effect on the disclosure of biological assets but does not significantly increase the disclosure of biological assets. the value of the company's growth coefficient is 0.006 which can be concluded that the company's growth increases by 1, which affects the increase in the disclosure of biological assets by 0.006. This effect is very small, and also has a significant level of 0.8910 > 0.05 which means that the increase in the growth of the company cannot affect the amount of disclosure of the company's biological assets in the financial report. Therefore, the growth of the company will increase the disclosure of biological assets if it is supported by other factors such as the number of biological assets and the accounting records policies that apply to the company. Company growth does not significantly affect the disclosure of biological assets, in line with the research of (Hayati & Serly, 2020) which has a positive influence on the disclosure of biological assets, but it is contrary to the research of (Carolina et al., 2020). Effect of Auditor Type on Biological Asset Disclosure Based on the results of the study, the type of auditor has a positive and significant effect on the disclosure of biological assets. Based on agency theory, company owners trust data audited by auditors of public accounting firms who are known and have a high degree of independence. It can be seen in the research sample that the majority of plantation & crops companies have used the services of big-four KAP in examining financial statements, which means that the level of auditing of financial statements is higher, including disclosure of biological assets. The financial information examined by the Big Four auditors also resulted in a reduced information gap between the owner of the company and the management of the company. In addition, the complete disclosure of information can increase the credibility of the annual report owned. These results agree with research conducted by (Alfiani & Rahmawati, 2019) which concludes that the type of auditor has a significant influence on the disclosure of biological assets. However, in contrast to the research of (Carolina et al., 2020; Gonçalves & Lopes, 2014) that the type of auditor does not influence the disclosure of biological assets. Effect of Public Ownership on Disclosure of Biological Assets The research shows that the results of public ownership have a negative and insignificant effect on the disclosure of biological assets. The coefficient value for public ownership is -0.162 which can be concluded that if every increase in the number of public ownership is one, there is a decrease in the disclosure of biological assets in the financial statements by 0.162. However, the public ownership variable has a prob-value greater than the level of significance (0,891 > 0,050). This indicates that public ownership has no significant effect on the disclosure of biological assets. The public who invest in companies are generally investors who tend to be small, for example, the community. Public owners cannot change or provide input to the management of the company as a whole so that there is no significant difference in the amount of demands for disclosure of financial information including disclosure of biological assets. Based on agency Biological Asset Disclosure in Indonesia Aminah, Suhardjanto, Rahmawati, Winarna, and Oktaviana 405 | Ilomata International Journal of Tax & Accounting https://www.ilomata.org/index.php/ijtc theory, company owners who have a larger percentage get greater authority to regulate management to disclose financial information for their benefit. CONCLUSION The purpose of this study was to determine the effect of the intensity of biological assets, company growth, type of auditor, and public ownership on the disclosure of biological assets. The following are the results of this study. 1. The intensity of biological assets has a positive and significant effect on the disclosure of biological assets. 2. The growth of the company has a positive and insignificant effect on the disclosure of biological assets. 3. The type of auditor has a positive and significant effect on the disclosure of biological assets. 4. Public ownership has a negative and insignificant effect on the disclosure of biological assets. For further research, it is hoped that more samples can be taken, thus strengthening the research. Then researchers can also add to the determinants of companies related to the disclosure of biological assets, such as company size, and concentration of ownership. Then, companies are expected to increase the completeness of disclosure of their company's biological assets by PSAK 69 by disclosing more detailed information related to agricultural activities, so that they can provide clearer information and become an added value for those in need. REFERENCE Alfiani, L. K., & Rahmawati, E. (2019). Pengaruh Biological Asset Intensity, Ukuran Perusahaan, Pertumbuhan Perusahaan, Konsentrasi Kepemilikan Manajerial, dan Jenis KAP Terhadap Pengungkpan Aset Biologis (Pada Perusahaan Agrikultur yang Terdaftar di Bursa Efek Indonesia Periode 2014-2017). 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