THE IMPACT OF DEBT STRUCUTRE, OPERATIONAL CAPABILITY, LIQUIDITY, PROFITABILITY, AND CAPITAL STRUCTURE TOWARD FINANCIAL RISK (CASE RESEARCH : PT. GAPURA ANGKASA)

Bayu Indra Wibiksana, Sylviana Maya Damayanti

Institut Teknologi Bandung

Abstract

In order to finance its operations and investment activities, one of PT. Gapura Angkasa's funding sources is debt, a kind of external funding for the company. Debt policy in a company is very important to be evaluated and analyzed properly because many companies will experience success with accuracy in making debt decisions. Debt policy can have an impact on optimizing the use of funds in the company. A company's financial troubles and likelihood of filing for bankruptcy may be impacted by its level of debt. The objective of research is for investigate the impact of debt structure, operational capability, liquidity, profitability, and capital structure on financial risk. This research utilizes secondary data sources in the form of financial reports from companies. The data utilized is PT. Gapura Angkasa's financial report data from 2017 to 2021. In this research, the independent factors include debt structure, operational capability, liquidity, profitability, and capital structure, whereas the dependent variable is financial risk. This research employs multiple regression with the aid of the SPSS application for its data analysis. Accordingly to the findings of the research, debt structure got a negative impact on financial risk. Similarly, operational competency negatively impacts financial risk. However, neither liquidity nor profitability nor capital structure had any impact on financial risk. The debt structure should be a concern for PT. Gapura Angkasa's management in order to retain the usage of debt while ensuring that the company's debt is not excessive and that its working capital continues to grow.

Keywords: Debt Structure, Operational Capability¸ Liquidity, Profitability, Capital Structure, Financial Risk

Introduction

PT Gapura uses debt, an external firm funding source, to finance its operations and investment activities. Dang et al. (2020) found that a company's debt structure was one of many elements that contributed to an increase in the degree of risk they faced, thus it is crucial that PT Gapura's management assess the quantity of debt it now carries, given the company's present financial situation. Since debt has such a profound effect on business outcomes, a thorough examination is required before any debt is taken on by the organization. The more a company's debt, the greater its exposure to insolvency or danger. Because of the potential for negative effects on the company's worth, businesses must exercise more caution when they formulate their debt policies. A company's vice president is responsible for carrying out the company's debt policy since this policy has the potential to influence the vice president and his managers' discipline with regards to the most efficient use of the company's finances. When a business takes on too much debt, it puts itself at danger of running into financial trouble and maybe going bankrupt. Because PT Gapura's debt ratio is much higher than that of its nearest rival, PT CAS,Tbk, the company's debt policy by its management is worth digging into. You can see how each firm's debt stacks up in the following chart.

Figure 1 Debt Ratio of PT Gapura Angkasa and PT CAS, Tbk

Based on Figure 1.1, it can be explained that the debt ratio between PT Gapura Angkasa and PT CAS, Tbk is relatively the same in 2017-2020, but different conditions occur in 2021, where the debt ratio level of PT Gapura Angkasa reaches 23.51 or in other words the amount of debt of PT Gapura Angkasa is 23 times greater than the company's equity value. From the point of view of the company's business risk, PT Gapura Angkasa is in a high-risk condition, because large debts will provide a high liability burden to creditors and interest expenses that must be paid, which has an impact on reducing the company's net profit. If this condition is not anticipated properly by company management, not only does the company have the potential to experience losses, but the company also has the potential to experience bankruptcy.

Besides from debt factors, according to Dang et al (2020) operational capability, liquidity and profitability can also affect the company's financial risk. Successful businesses often have the resources to pay off debts and manage other financial concerns. In order to keep the firm functioning smoothly, a sufficient amount of cash on hand is required for routine tasks, emergency planning, and the initiation of measures to boost performance. Companies with a high degree of liquidity are less likely to default on their loans since they can meet all of their debt commitments, especially those that are coming due in the near future. In addition, a company's capacity to create profits may have a beneficial influence on risk management by allowing it to pay down debt and build up equity by keeping more of its earnings.

Next, based on the internal risk assessment of PT Gapura Angkasa, there are two aspects of the company's current high-risk business activities. Two of these are related to the aspect of Enhancing Financial Stability, this is because the dependence on the parent company, the condition of the main stakeholders and customers, namely PT Garuda Indonesia, has not fully recovered after the PKPU, the impact of BRI's SCF interest expense and the increase in GSE CIMB Niaga Syariah lease payments, the risk of increasing receivables & payables and business development aspects. PT Gapura's risk profile can be seen in the figure below.

Figure 2 Risk Assessment of PT Gapur Gapura Angkasa

Source: PT Gapura (2022)

PT Angkasa Pura II owns 46,62% of PT Gapura, and PT Garuda Indonesia owns 45,62%, and PT Angkasa Pura 1 owns 7,76%/.

Figure 3 Shareholder of PT Gapura Angkasa

PT Gapura in running its business is led by one President Director who is also the Director of Finance and Risk Management, and three directors, respectively Director of Operation of Engineering, Director of Human Capital of Corporate Strategy, and Director of Commercial and Business and Development.

Figure 4 Organizational Structure of PT Gapura Angkasa

Effective corporate management, according to the findings of Nenu et al. (2018), plays a crucial role in mitigating financial risk by way of debt structure policies. When a corporation has a high debt ratio, it increases its exposure to risk. As a result of inefficient management, a growing debt load may have a negative impact on a business. Nenu et al. (2018) revealed that debt structure has a very beneficial impact on financial risk. Dang et al. (2020) came to similar conclusions, highlighting the importance of debt's effect on company financial risk.

Good operational capability of the company will reduce financial risk because this operational strength will greatly affect the ability to grow in the future. The effectiveness of asset turnover, asset operations, asset management, and other aspects all contribute to the asset's operational capabilities. When a firm has solid operational skills, it may increase its profits, which provides reassurance of its financial health and mitigates dangers to its bottom line. Cao and Zeng (2005) discovered a negative correlation between operational capability and financial risk.

In business, liquidity is defined as the capacity to meet current and future obligations (including principal and interest). Current ratio is a measure of liquidity. Current ratio is a measure of liquidity. To reduce financial risk and increase the possibility of timely loan repayment, a corporation should maintain a high level of liquidity. According to CHau's (2017) analysis, financial risk increases as liquidity decreases.

A lower amount of financial risk is experienced by a business when its profitability, as measured by return on assets, is high. In general, financial risks are reduced when a company's profitability, or the profit it earns from its operations and output, increases. Both Cao and Zen (2005) and Bhunia and Mukhuti (2012) found a negative relationship between company financial risk and profit.

As a ground handling service provider for airlines operating in Indonesia, PT Gapura Angkasa requires maximum funding in the company's business operations. Moreover, the company's core business requires the support of a sufficient number of human resources, and good infrastructure with advanced information technology. These conditions require companies to fund the company's business operations by utilizing external loans. However, too much debt will cause interest expense and erode company profits, thus potentially causing the risk of bankruptcy (Dang et al, 2020). This is currently being experienced by PT Gapura Angkasa, where the condition of the company's debt structure is quite large, reaching 2.7 times higher than capital in 2020, and jumping to 23 times higher than capital in 2021. The level of debt ratio that is uncontrollable or far above capital, if not managed carefully, will create financial risks for PT Gapura Angkasa.

The high potential financial risk faced by PT Gapura Angkasa is also in line with PT Gapura Angkasa's internal risk assessment, which concludes that the company's current business activities are high risk. In particular, with regards to growing financial security, decreasing reliance on the parent company, acquiring and retaining new clients, the possibility of expanding accounts receivable and payable, and other factors of expanding the firm.

Research Method

1. Data Collection Methods

The financial reports of companies are used as secondary sources of information for this analysis. Data that is secondary is data that is already in existence or data that is controlled by a third party. Data collection is done by recording any data needed in the company's annual report. The data used is financial statement data from 2017 to 2021 sourced from PT Gapura Angkasa.

The research variables of this study consist of independent and dependent variables, To be able to do data processing, these variables need to be operationalized. The variables used in the study are:

a. Variabel Independen

Variables that do not directly impact the dependent variables but do cause changes or events to occur are called independent variables (bound). The independent variables used in this study are debt structure (X1), operational capability (X2), liquidity (X3), profitability (X4), capital structure (X5).Variabel

b. Variabel Dependen

Dependent variables are variables that are often referred to as output variables, criteria, consequences. The dependent variable used in this study is financial risk.

Table 1 Variable Operationalization

Research Variables	Indikator	Scale
Fiancial Risk Source: Dang et al (2020)	FRit = SZLit + SYit + GLit + YFit + YZit FRit is the value measuring financial risk of index, We took it as dependent variable in this paper. SZLit = (profit before tax + depreciation + deferred tax) / current liabilities SYit = Pre-tax profit/operating capital. GLit = Shareholders’ interests / current liabilities YFit = Net tangible assets / total liabilities YZit = Working capital / total assets.	Ratio
Debt Structure Source: Dang et al (2020)	Debt Structure = Short-term Debt/total Debt	Ratio
Oporational Capability Source: Dang et al (2020)	Turnover Receivable = Annual Credit /Recevaible	Ratio
Liquidity Source: Dang et al (2020)		Ratio
Profitability Source: Dang et al (2020)		Ratio
Capital Structure Source: Dang et al (2020)	CS = Total Equity / Total Assets	Ratio

c. Research Methods

This study use a causal or explanatory design, a quantitative methodology, to determine how one variable influences or is accountable for changes in other variables (Cooper and Schindler, 2017). This research uses debt structure, operational capacity, liquidity, profitability, and capital structure as independent factors, and financial risk as the dependent variable.

3. Data Analysis Technique

In this study, we use the SPSS software to do multiple regression on our data. Before conducting multiple regression and hypothesis analysis, descriptive statistical testing was first carried out.

a. Descriptive Statistics Test

A distribution (data) is a calculation of values from the lowest value to the highest value, resulting from the tabulation of incidents. Descriptive statistical measures are used to describe the center, spread, and shape of the distribution and are helpful as an initial tool for data description (Cooper and Schindler, 2017). The distribution of data may be described using the standard deviation, extreme values, and middle values. More dispersed data is represented by a bigger standard deviation. The distribution of metric variables may be described by the standard deviation, the maximum value, and the lowest value.

b. Linear Regression Test

First, multiple regression is utilized to create a self-weighting estimating equation to predict values for the dependent variable based on values for one independent variable (Cooper and Schindler, 2017). Second, excluding potentially influencing factors allows for more accurate evaluation of other factors' importance. In order to put hypotheses of causation to the test and provide an explanation for them, third. Regression is utilized not just as a descriptive tool but also as an inference tool to test hypotheses and estimate populations.

The financial risk is the dependent variable, while the independent factors are the debt structure, operational capabilities, liquidity, profitability and capital structure. The study's basic regression model may be expressed in the form of an equation, as follows:

Model

Y = α + β₁X₁+ ε

Y = α +β₂X₂ + ε

Y = α + β₃X₃+ ε

Y = α +β₄X₄ + ε

Y = α +β₅X₅ + ε

Description:

Y = Financial Risk

α = Constant

β₁ – β₃ = Regression coefficient of each independent variable

X₁ = Debt Structure

X₂ = Opeartional Capability

X₃ = Liquidity

X₄ = Profitability

X₅ = Capital Structure

e = error term / confounding factors

Hypothesis Test

The following procedures were carried out in order to demonstrate the validity of the hypothesis: T-test (Hypothesis Test) and coefficient of determination analysis. In this research, we will utilize the t test and the coefficient of determination to assess the relative importance of the independent variables in explaining the dependent variable.

1. Partial Hypothesis Test with t Test

a. Determining ttable

To determine the t table, first determine the df (degree of freedom). In this study, the α determined is 5%. df is obtained from the formula (n-k) or the amount of data minus the number of variables.

b. Determining t count

In order to calculate the t-count, we use SPSS for Windows Version 24.00 as our primary data processing application.

Description

c. Comparing t count with t table.

To determine the acceptance or rejection of the hypothesis with the following conditions:

d. Decision Making

A decision is reached based on the outcome of comparing the t count to the t table. The n-k rule is used at the 5% (error rate of 0.05) or 95% (confidence level of 0.95) level to calculate the t-table. Therefore, if a variable has an error rate of greater than 5%, it is ruled out as a relevant factor (Cooper and Emory, 2008).

Determination Coefficient Test

Malhotra (2017) defines R2 as the fraction of total variation in Y that can be attributed to variation in X, and claims that R2 measures the degree of link between two variables. Additionally, Malhotra (2017: 535) Coefficient of determination (R2) is multiplied by the number of independent variables and the size of the sample to account for declining returns, yielding the adjusted R2. The contribution of new independent variables decreases rapidly once the first few are taken into account.

Research Findings and Discussion

1. Descriptive Statistical Analysis

In this study, we use descriptive statistics to compute the range of values included in the data as well as their means, medians, and standard deviations. Table 1 displays the results of descriptive statistical testing for all variables.

Table 1 Descriptive Statistical Test Results

	FR	DER	OPC	LIQ	PROF	CS
Mean	1.815720	0.668960	0.300472	1.648300	0.138300	0.382220
Maximum	2.3733	0.7696	0.4129	2.2459	0.4727	0.5212
Minimum	1.4329	0.5933	0.1774	0.6103	0.0134	0.0408
Std. Dev.	0.3954948	0.0657310	0.0918343	0.6282301	0.1885841	0.1971352

Source: Results of Data Processing with SPSS 24 (2022)

Description:

Y : Financial Risk (FR)

X1 : Debt Structure (DER)

X2 : Operational Capability (OPC)

X3 : Liquidity (LIQ)

X4 : Profitability (PROF)

X5 : Capital Structure (CS)

Based on the descriptive statistical test table above, information is obtained that:

a. Financial Risk (Y)

An analysis of the data shows that the median value of the financial risk (FR) variable is 1.815720, with a maximum of 2.3733 in 2017 and a low of 1.4329 in 2020. When a variable's standard deviation is 0.3954948, it signifies that the greatest allowable increase in the mean is that much. The largest reduction in the average financial risk (FR) variable is -0.3954948, while the maximum rise is +0.3954948. Because the standard deviation of the percentage change is so much less than the mean, this data explains why PT Gapura Angkasa's financial risk is so low. This shows that PT Gapura Angkasa is quite strong against external shocks. This condition can be seen from the covid-19 pandemic that hit Indonesia in the beginning of 2020, which made PT Gapura Angkasa business sluggish but not too significant. Things like this show that PT Gapura Angkasa is ready to face risks or control of risks by the management of PT Gapura Angkasa is quite optimal.

b. Debt Structure (X1)

The processed data shows that the DER debt structure variable has a mean or average value of 0.668960, with a maximum value of 0.7696 in 2021 and a minimum value of 0.5933 in 2017. As the highest rise in the mean variable, with a standard deviation of 0.0657310. Debt Structure (DER) increases by +0.0657310, whereas the maximum DER decline is -0.0657310. These findings show why PT Gapura Angkasa's debt consumption is relatively high risk, the portion of the company's short-term debt is more than 50% of long-term debt. This indicates that the firm needs a healthy cash flow in order to meet its immediate financial commitments.

c. Operational Capability (X2)

The data analysis shows that the operational capability (OPC) variable reaches a high of 0.4129 in 2020 and a low of 0.1774 in 2017. The mean value of the OPC variable is 0.300472. Maximum rise in the average variable with a standard deviation of 0.0918343. Increases in OPC amount to +0.0918343, while decreases in OPC may go as low as -0.0918343 on average. According to these calculations, PT Gapura Angkasa has a high degree of competence, as shown by the fact that the standard deviation of its gains and losses is much less than the mean.

d. Liquidity (X3)

The processed data shows that the average value of LIQ is 1.648300, with a high of 2.2459 in 2019 and a low of 0.6103 in 2021. The highest increase in the mean variable is 0.6282301, according to the standard deviation. The average liquidity variable (LIQ) decreases by a maximum of -0.6282301, while the liquidity rise is +0.6282301. Liquidity ratio of 1.648 indicates that current assets are more than current debt, therefore the firm has the capacity to cover its short-term commitments, which explains why PT Gapura Angkasa has a relatively high liquidity level on average.

e. Profitability (X4)

The data analysis shows that the profitability variable (PROF) ranges from 0.0134 in 2019 to 0.4727 in 2021, with an average value of 0.138300. With a standard deviation of 0.1885841, it indicates a significant increase in maximum relative variability. Profitability goes up by +0.1885841, whereas the average profitability of the company may go down by no more than -0.1885841. These results explain that on average PT Gapura Angkasa's ability to generate ROA per year of 0.138300 is still relatively low because it is still very far below the risk free value of 4.25% (BPS, 2022). Or in other words, PT Gapura Angkasa has not succeeded in maximally utilizing its potential assets to generate returns.

f. Capital Structure (X5)

The processed data shows that the capital structure (CS) variable has a mean or average value of 0.382220, with a maximum value of 0.5212 in 2019 and a lowest value of 0.0408 in 2021. The highest allowable rise in the mean variable has a standard deviation of 0.1971352. An rise of +0.1971352 in capital structure (CS) is possible, with a maximum fall of -0.1971352 in the average CS variable. These results explain that the level of capital structure of PT Gapura Angkasa is quite good, because on average the company's total debt is only about 38% of total equity, or the company's equity is greater than debt so as to provide confidence to creditors that the company has the ability if it will issue new debt.

2. Linear Regression Analysis

In this research, we use a linear regression test to explore how factors including debt structure, operational capacity, liquidity, profitability, and capital structure influence financial risk. Table 4.2 displays the outcomes of the linear regression analysis.

Table.2 Linear Regression Test Results

Variable	Coefficient	t	Sig.
DER	-4,159	-4,219	0,001
OPC	-2,361	-3,405	0,003
LIQ	0,138	0,982	0,339
PROF	-0,468	-1,044	0,310
CS	0,616	1,435	0,169

Source: Results of Data Processing with SPSS 24 (2022)

The negative coefficient of -4.159 and the significance level of 0.001 alpha 0.05 in Table 2 above suggest that the debt structure variable has a negative and statistically significant influence on financial risk. With a coefficient of -2.361 and a significance level of 0.003 at alpha = 0.05, the study concludes that operational capability has a negative and statistically significant influence on financial risk. In addition, with a 0.138 coefficient value and a 0.339> alpha 0.05 significance level, liquidity has no influence on financial risk. Because the profitability variable has a -0.468 coefficient and a significant value of 0.310> alpha 0.05, it has no bearing on the level of financial risk. The final capital structure variable, with a 0.169> alpha 0.05 coefficient value, has no influence on financial risk.

3. Business Solution

An actionable business solution for PT Gapura Angkasa may be defined based on findings from hypothesis testing using multiple linear regression on the impact of debt structure, operational capacity, liquidity, profitability, and capital structure on financial risk.

a. The Effect of Debt Structure on Financial Risk

The first hypothesis demonstrates that the debt structure acquired a t count value of -4.219> 0.726 and a significant value of 0.001 <0.05. According to these findings, PT Gapura Angkasa's financial risk increases from 2017 to 2021 as a consequence of the company's debt structure.

Investment decisions taken by companies cannot be separated from financing decisions. One of the alternative financing is from debt. Financing by debt will affect the company's capital structure. Investment and funding decisions cannot be separated from the possibility of risks arising. According to Effendy et al. (2019), shareholders tend to demand a higher rate of return and see a company's financial risk as higher if its debt levels are elevated. The results of this research show that debt structure increases financial risk. The findings here corroborate those of Dang et al. (2020), who discovered that debt structure is related to financial risk. These results explain that an increase in short-term debt at PT Gapura Angkasa can reduce the level of financial risk, this can be caused by the nature of the business carried out by PT Gapura Angkasa, where the level of cash turnover is quite high, so that an increase in short-term liabilities does not really disturb the company's financial condition.

b. Effect of Operational Capability on Financial Risk

According to the second hypothesis, the estimated t value is -3.405> 0.726, and the significance level is 0.003 0.05, indicating that the coefficient value is -2.361 and the association is negative. The data for PT Gapura Angkasa's financial risk from 2017-2021 shows a negative correlation between operational capacity and risk.

In this study, operational capability is measured using the receivable turnover ratio. In theory, good receivable turnover has a high turnover rate (Wulandari, 2017). PT Gapura Angkasa has an increase in total receivables every year, where the high level of receivable turnover has a good impact because the working capital invested in receivables is getting lower. So this prevents the company from occurring financial risk, because this means that less working capital is used in accounts receivable turnover. This study's findings corroborate those of Dang et al. (2020), who discovered an inverse relationship between operational capacity and financial risk.

c. Effect of Liquidity on Financial Risk

As for the third hypothesis, we find that there is a positive correlation between liquidity and other variables (t=0.982>0.726, t=0.339>0.05), indicating that the coefficient value is 0.138. According to these findings, PT Gapura Angkasa's financial risk does not increase throughout the timeframe of 2017-2021 while liquidity is high.

Having sufficient liquidity indicates that a business can meet its short-term financial commitments. Predicting when money will be needed, particularly in an emergency, is one of the main advantages of using the liquidity ratio. If a business has enough of cash on hand, it can easily cover its obligations. In this analysis, liquidity was determined by calculating the current ratio (current assets to current liabilities), which indicates whether or not a firm can pay its short-term debt with the resources available right now. Short-term liabilities for PT Gapura Angkasa rise in the observation year, followed by rising current assets. The company's exposure to financial risk will therefore be reduced. Contrary to the findings of Dang et al. (2020), this analysis shows that liquidity does not increase financial risk.

d. Effect of Profitability on Financial Risk

The t-value of -1.044> 0.726 and the significance level of 0.310> 0.05 indicate that the coefficient value of -0.468 indicates a negative association between profitability and t. According to these findings, PT Gapura Angkasa's financial risk will neither increase or decrease depending on the company's performance between 2017 and 2021.

The profitability ratio evaluates a company's capacity to turn its assets, capital, and sales into profits. Nasar and Krisnando's (2020) study shows that a higher return on assets (ROA) indicates a more efficient use of a company's assets; in other words, with the same number of assets, the profit that may be made is significant, and vice versa. This study also disproves the "pecking order" theory, which proposes that companies with high profit levels should prioritize using their internal funding sources to meet operational needs, rather than turning to debt or external funding, to reduce the likelihood of bankruptcy and the cost of servicing debt (Supeno, 2022).

e. The Effect of Capital Structure on Financial Risk

The t-value of 1.435> 0.726 and the significance level of 0.169> 0.05 indicate that the fifth hypothesis about the link between the capital structure and the firm's performance is correct. Based on these findings, it seems that PT Gapura Angkasa's capital structure does not have a role in the company's financial risk throughout the years 2017-2021.

Capital structure decisions are important because it affects profitability and solvency. To reduce industrial capital expenditures as little as possible, the optimal capital structure combines various forms of loan and equity. Capital structure is defined by Sartono and Nasar (2020) as the mix of common stock, preferred stock, preferred debt, and unsecured debt that a company has on its books permanently. Companies' success or failure has been linked to a variety of factors, including their capital structure. Management of capital structures is performed with the goal of decreasing financial risk. With the correct framework, a company's debt and equity may be brought into harmony. So, it may aid businesses in controlling and lowering their financial risks. The study's findings, however, disprove the idea that capital structure is especially important for businesses, as high and low capital structures have a direct impact on a company's financial condition and, by extension, its value. According to Hau (2017), there should be an inverse link between financial risk and capital structure, however these findings contradict that.

Conclusion

The following conclusions are drawn from this study based on the findings of the data analysis presented in the preceding chapter and in an effort to address the issues raised by this research. 1. Debt structure has a negative effect on financial risk at PT. Gapura Angkasa for the period 2017-2021 2. Operational capability has a negative effect on financial risk at PT. Gapura Angkasa for the period 2017-202. 3. Liquidity has no effect on financial risk at PT. Gapura Angkasa for the period 2017-2021 4. Profitability has no effect on financial risk at PT. Gapura Angkasa for the period 2017-2021 5. Capital structure has no effect on financial risk at PT. Gapura Angkasa for the period 2017-2021

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