Analysis of the Effect of Profit Accounting, Economic Growth, Interest Rates and Capital Structure on Share Prices in Property and Real Estate Companies

Economic growth signifies a period marked by an increase in real national income or real gross national product. This study aims to assess the effects of accounting profits, economic growth, interest rates, and capital structure on share prices within the financial statements of property and real estate firms listed on the Indonesia Stock Exchange. Utilizing secondary data, the sample comprises 11 property and real estate firms listed on the Indonesia Stock Exchange over a five-year period. Employing purposive sampling, the research period spans five years. Multiple regression analysis is employed as the analytical method. The findings reveal a positive correlation between capital structure and accounting profits with stock prices, whereas economic growth and interest rates do not significantly influence stock prices. This research underscores the importance for companies to prioritize factors influencing stock prices.


Introductions
In the era of globalization, property and real estate companies play an important role in Indonesia's economic landscape.(Ravelita, 2020).The government consistently promotes the improvement of facilities and infrastructure to increase the growth rate.(Aldy Cornelius, 2019).Stock prices observed on the exchange are influenced by market participants and the dynamics of supply and demand in the capital market.(Ramandei et al., 2023).Investors if they want to invest in stocks need accurate information (Khairani, 2021).
The generally accepted definition of profit in the current accounting framework is accounting profit, which represents the variance between measured revenue and costs.(Aldy Cornelius, 2019).Previous research has shown that accounting profit does not have a significant influence on share prices in property and real estate companies, as per research findings.Instead, the results show that an individual's net income has a significant impact on the stock price.(Sari & Muslih, 2022).The second factor affecting stock prices is economic growth.Economic growth is the stage at which there is an increase in real national income or real gross national product.(Ariani & Rochdianingrum, 2023).According to previous research Economic growth has no effect on the Stock Price Index.Based on previous research, it was found that economic growth has a significant positive impact on stock prices.(Ariani & Rochdianingrum, 2023).
Interest rates are a significant factor affecting stock prices, exerting a major impact on competition between stocks and bonds in the capital market.When interest rates rise, investors tend to sell stocks in favour of bonds, leading to the next drop in stock prices.Basically, the interest rate reflects the fee paid to borrow a currency over a certain duration.(Dini Imran, 2022) .According to previous research (Pramastya, 2022) explain Interest rates have a positive and insignificant effect on stock prices.While previous research according to (Dini Imran, 2022) State that interest rates have a negative and significant influence on stock price.The fourth factor, namely the influence of capital structure on the share price of the capital structure in a company is used to compare between capital sourced from creditors and sourced from shareholders (Murtiningtyas et al., 2023).The capital structure to some degree does not keep up with the increase in share price.(Ramandei et al., 2023).However, stock prices that use debt are riskier than not using debt (Salsabila & Ardini, 2022).
Based on previous research and the background that has been discussed this research aim to analysis of the effect of accounting profits, economic growth, interest rates and capital structure on stock prices.This research using sample in property and real estate companies in 2018-2022.
Accounting Profit (Kusuma & Sumadi, 2021) Profit is a measuring tool used to measure the performance of a company and shows the responsibilities and obligations of top management in managing the resources that have been given to it.According to (Aldy Cornelius, 2019).(Aldy Cornelius, 2019) Accounting profit is defined as an economic increase during an accounting period caused by an increase in assets and a decrease in liabilities, which can result in an increase in equity that does not come from investment contributions.Syntactically, accounting profit is the result of a comparison of revenues and expenses, or the difference in income and expenses based on the principle of adequate realization (Ilmiyono et al., 2017).

Economic Growth
The level of output resulting from economic activity each year is called economic growth.(Kapaya, 2020).Economic growth will drive financial growth, which means demand for financial services will increase.While according to (Tan & Mohamad Shafi, 2021) It empirically claims that a good stock market can lower transaction and information costs, promoting economic growth.Economic growth can be measured by the magnitude of GDP.(Ariani & Rochdianingrum, 2023) Businesses that thrive to produce goods or services that improve people's welfare are called economic growth.

Interest
The interest rate is a component of the cost of the loan that must be paid when requesting a loan from the fund.(Terayana & Triaryati, 2018).says that the cost incurred by the borrower to get cash from the lender is represented by the interest rate.(Khoiri, 2022).According to (Khairani, 2021) When loan interest increases, it will increase the credit interest expense and decrease net profit.(Yunita & Robiyanto, 2018) High interest rates affect stock prices because they cause investors to turn to safer instruments such as deposits and sell shares they own riskwise.The higher the interest rate, the higher the interest cost, which can reduce the company's profits.

Capitalization Structure
(Borges Júnior, 2022) A company's capital structure can be defined as the arrangement of its funding sources, which includes loans and own capital from affiliated businesses.As stated by (Suryana, 2021) The capital structure of the enterprise is established taking into account the advantages of tax deductions.According to him, long-term debt is a type of long-term finance with a maturity of more than a year.(Isnaini, 2019).While according to (Salsabila & Ardini, 2022) capital is a consideration of the amount of short-term debt, long-term debt.

Share Price
According to (Pratiwi, 2020) The stock price serves as a key metric of a company's success, as a higher stock price offers several advantages, notably capital (Liantanu et al., 2023).Market participants establish prices within the stock exchange at specific intervals, and the interplay between supply and demand in the capital market also exerts influence (Jogiyanto, 2016: 96).If the company cannot optimize its performance and does not make a profit, the stock price will fall.(Amri & Subardjo, n.d.).

The Effect of Accounting Profit on Stock Prices
According to research (Wulandari & Wahyono, 2021) The results showed that accounting profit variables affect stock prices.Meanwhile, according to research (Ravelita, 2020) Accounting profit has a positive and insignificant influence on stock prices.H1 : Profit accounting affects stock prices.

The Effect of Economic Growth on Stock Prices
According to Economic Growth (GDP) Research (Sukmawati et al., 2020) Some do not have a significant effect on stock prices, while according to (Ariani & Rochdianingrum, 2023) Economic growth research has an effect on stock prices.H2 : Economic Growth has no effect on stock prices.

The effect of interest rates on stock prices
According to research (Amanberga & Abdi, 2022) Interest rates have a negative and significant effect on stock prices, while according to While (Terayana & Triaryati, 2018) Interest rates have no effect on the stock price index.H3 : Interest rates have no effect on stock prices.

The effect of the level of capital structure on the share price
According to research (Suryana, 2021) In part, capital structure has no effect on stock prices, while research shows (Isnaini, 2019) Capital structure has no effect on the share price.H4 : The Level of Capital Structure Affects Stock Prices.

Population and Sample
Companies in The population and sample of this study consist of companies operating in the real estate and property sector, which were listed on the Indonesia Stock Exchange during the period from 2018 to 2022.The sample used in the study is purposive sampling because this sampling approach is used to sample the population based on predefined criteria, as stated by (Isnaini, 2019).Sampling is determined using several sample criteria, which are as follows: 1. Property and real estate firms listed on the Indonesia Stock Exchange (IDX).2. Companies that consecutively report annual financial statements.3. Companies that earned consecutive profits.

Data Source Type
The researchers utilized secondary quantitative data sourced from property and real estate firms listed on the Indonesia Stock Exchange.This data was extracted from the companies' annual financial reports, chosen for their comprehensive insights into the firms' financial performance as listed entities.Access to the financial statements of these property and real estate firms was facilitated through the official website of the Indonesia Stock Exchange (IDX), available at www.idx.co.id.

Data Collection Techniques
The researcher's method for collecting data for the study was a literature review, which included a literature review, literature review, and other similar sources.Additionally, secondary data were gathered from diverse sources, encompassing the official website of the Indonesia Stock Exchange (IDX) and company records, along with the annual financial reports of property and real estate firms spanning the years 2018 to 2022.(Pratiwi, 2020) Secondary learning, classification, and data analysis-such as reviewing a company's annual financial statementsare methods of data collection accompanied by documentation techniques.

Data Analysis Techniques
Test Asumsi Classic (Isnaini, 2019) The purpose of traditional assumption tests is to obtain accurate findings that can also be understood by the examiner.This is done because not all data can be used using regression, which prevents inaccurate estimates.There are four traditional assumption tests: tests for heteroskedastic, autocorrelation, multicollinearity, and data normality.

Multiple Linear Regression Analysis
The goal of multiple linear regression analysis is to predict the average population or mean value of the dependent variable based on a set of known values of the independent variable(s).It examines how the dependent variable (if t) depends on one or more independent (independent) variables.(Ravelita, 2020).The following model equation: The t test can be said to be a partial test, which is a hypothesis test that can serve as an indication of how far the influence between the variables of economic growth ratio, accounting profit, interest rates and structure on the independent variable (dependent), namely stock price.This t test can be performed with a significant magnitude level of 5% or 0.05.Some of the requirements for t-tests include: (10). 1.If the significance level of t is less than 0.05, then Ho is rejected, indicating a significant effect of the independent variable on the dependent variable.2. Conversely, if the significance level of t is greater than 0.05, then Ho is accepted, suggesting no significant effect of the independent variable on the dependent variable.

Test F
The F-test is used to assess the validity of multiple linear regression models.In performing the F-test at the significance level α = 5%, several criteria are considered: 1.If the significance level of the F-test exceeds 0.05, it indicates acceptance of the hypothesis, suggesting that all independent variables collectively exert a significant influence on the dependent variable.2. Conversely, if the significance level of the F-test is below 0.05, the hypothesis is rejected, indicating that all independent variables jointly possess a significant impact on the dependent variable.
Test Coefficient of Determination (Khairani, 2021) The coefficient of determination, or R-squared (R 2 ), quantifies the degree to which a model can account for variations in the dependent variable.A low R 2 value indicates that the independent variable has limited ability to clarify changes in the dependent variable.R 2 values fall between zero and one (0 < R 2 < 1), where: (1) R 2 nearing 1 signifies that the independent variable supplies nearly all the information necessary to forecast the dependent variable.
(2) Conversely, an R 2 value close to zero indicates that the independent variable offers minimal data to estimate the dependent variable.

Normality test
To determine if the data distribution resembles or follows the normal distribution, one might perform a normality test.Regression analysis, which measures relationships or entanglements between independent variables, is based on classical principles.The classical assumption test consists of forty (four) tests: heteroskedastic, autocorrelation, multicollinearity, and normality data.(Pratiwi, 2020).

Multicorrelation Test
The objective of multicollinearity testing is to examine potential linear relationships among independent variables within a regression model.To offer further context, the outcomes of the multicollinearity test are depicted in the table provided below.

Table 1. Multicorrelation Test
From Table 1., it is evident that none of the independent variables are affected by multicollinearity issues.This is evidenced by the Variance Inflation Factor (VIF) values being less than 10 and Tolerance values exceeding 0.10.For instance, Variable X1 demonstrates a tolerance value of 0.991 and VIF of 1.009, Variable X2 displays a tolerance value of 0.701 and VIF of 1.427, Variable X3 exhibits a tolerance value of 0.681 and VIF of 1.468, while Variable X4 portrays a tolerance value of 0.970 and VIF of 1.031.

Autocorrelation Test
The autocorrelation test examines whether there exists a correlation between residual errors in the current period (t) and errors from preceding periods (t-1) within linear regression models.The presence of autocorrelation can be determined through a run test.(Pratiwi, 2020).

Table 2. Autocorrelation Test
If the Durbin-Watson (D-W) statistic falls below dL or exceeds 4 -dL, it indicates the presence of autocorrelation in the data.Conversely, if the D-W statistic lies between dU and 4 -dU, the data does not exhibit autocorrelation.No definitive conclusion can be drawn if the D-W statistic falls within the range of dL to dU or 4 -dU to 4 -dL.
Taking into account a sample size of 59 (n) and 4 independent variables (k = 4), the Durbin-Watson statistic (DW) is calculated as 738 from the table provided.Then, this value is compared with the critical value of the significance table at a significance level of 5%.As a result, the du value of 7358 and the DW value of 738 are obtained.Since the value of DW 738 is less than the upper bound (du) 7358 and also less than (4-du), or 4-7358, it is possible to conclude that there is an autocorrelation.

Heteroscedasticity Test
Heteroscedasticity is used to assess inconsistent residual variation between observations.If there is no discernible pattern and the data points are uniformly distributed around zero on the Y-axis, it can be inferred that heteroscedasticity is absent.

T Test
The partial test (t) evaluates the degree to which the independent variable can account for individual variation.This assessment is conducted at a significance level of 5%.Referring to the data presented in table 3 above, the analysis shows that the impact of variable X1 on variable Y results in a significance value of 0.451, which exceeds 0.05.As a result, the alternative hypothesis (Ha) is rejected, and the null hypothesis (H0) is accepted, indicating that variable X1 has a partially insignificant influence on variable Y. Similarly, for variable X2, with a significance value of 0.755 exceeding 0.05, both Ha and H0 are accepted, indicating a partially insignificant influence of variable X2 on variable Y.The significance value for variable X3 is 0.686, also goes beyond 0.05, which leads to acceptance of Ha and H0, implying a partially insignificant effect of variable X3 on variable Y. Lastly, for variable X4, the significance value of 0.048 exceeds 0.05, leading to acceptance of Ha and H0, indicating a partially insignificant effect of variable X4 on variable Y.

Test F
The F-statistic evaluates the collective impact of the independent variables on the dependent variable.This analysis involves comparing the p-value to the significance level α (alpha).If the p-value is less than α (0.05), the null hypothesis (H0) is rejected, indicating a significant joint influence of the independent variables on the dependent variable.Conversely, if the p-value exceeds α (0.05), H0 is accepted, suggesting no significant collective influence of the independent variables on the dependent variable.The outcomes of the F-test are presented in Table 4 below.According to the data presented in table 4 above, the independent variable shows a P-Value of 0.310, which is lower than the conventional threshold of 0.05.Therefore, following the test criteria, when the probability value is less than 0.05, it shows that the variables X1, X2, X3, and X4 collectively affect profitability.

Test Coefficient of Determination
The assessment of the coefficient of determination aims to measure the proportion of variance in the dependent variable that can be explained by the independent variable, thus reflecting the extent of its impact.Referring to the data presented in Table 5, the coefficient of determination is represented by a adjusted R-squared value of 0.017.This suggests that, in this case, the capital structure accounts for about 17% of stock price fluctuations (Y).Variables or factors omitted from the model contribute to 83% (100% -17%) of the overall variance.

Conclusions
Drawing from the findings of data analysis, the following conclusions are derived: During the period spanning from 2018 to 2022, the impact of various factors on share prices within property and real estate companies has been investigated.Firstly, accounting profit variables have been identified to significantly influence share prices during this timeframe, indicating their importance in shaping market valuations.However, the influence of economic growth variables on share prices appears to be partial, suggesting a more nuanced relationship between economic indicators and market performance within the property and real estate sector.Similarly, the impact of interest rates on share prices is also observed to be partial, particularly within the timeframe from 2018 to 2019, implying that other factors may play a more dominant role during this period.Additionally, the influence of the capital structure on share prices is noted to some extent, indicating its significance in determining market valuations, particularly within the timeframe from 2018 to 2019.Moreover, a simultaneous impact of accounting profit, economic growth, interest rates, and capital structure variables on share prices within property and real estate companies has been observed during the period from 2018 to 2019, suggesting the interplay of multiple factors in driving market performance within the sector.Aldy Cornelius. (2019). Jurakunman Vol. 12, No. I, Jan. 2019ISSN : 2086-681X. 12(I), 9-24. Amanberga, A., &;Abdi, M. (2022).The effect of inflation, exchange rates, and interest rates on property company share prices for the 2018-2021 period.Journal of Managerial and

Figure 1 .
Figure 1.Normality test histogramAs seen in figure1, we can see the histogram pattern above, it can be concluded that the normality test histogram shows a normal distribution pattern.

Figure 3 .
Figure 3. Heteroscedasticity Test Based on figure 3 scatterplot, the dots are scattered randomly without forming any particular line, pattern, or trend.The graph illustrates that the data distribution centres around zero.The test outcomes indicate the absence of heteroscedasticity issues in this regression model, signifying that the variables examined in this study demonstrate homoscedasticity.