Corresponding Author: Lusia Sri Arini
E-mail: [email protected]
INTRODUCTION
In the business world
the company is doing various ways to develop its company. Such as innovating
its products to increase the competitiveness of the products produced,
expanding the business or expanding the market, improving the quality of human
resources and so on to face this competition. (Novione and Rusmala, 2016)
Companies in
expanding require additional capital. The financial manager must determine the
right source of funding, so that the optimal source of funding can be achieved.
Optimal funding should pay attention to the magnitude of the need for funds,
the level of return demanded by the fund owner, the length of attachment of
funds and the composition of funds. In general, the source of the company's
funds comes from debt and capital. This condition also affects how the company
determines funding choices.
Sources of funding
can come from internal or external. If the internal funds are insufficient, the
new company issues debt securities that can be used only to the maximum extent
and the last step is to issue shares. Thus, before deciding which source of
funds to use, the company's management conducts a comparative analysis of the
costs of the sacrifices that the company bears compared to those obtained from
each source of funds.
Classification of
company sources of funds from short-term sources of funds and medium/ long-term
sources of funds. The company's short-term sources of funds are used to fund
inventory needs or fund trade receivables. Short-term sources of funds derived
from loans are not used to fund long-term funding needs. Medium/long-term
sources of funds are used to fund the purchase of fixed assets or business
expansion (Toto Prihadi, 2013;13-14). This study is to analyze the determinants
of capital structure in industrial sector manufacturing companies listed on the
Indonesia Stock Exchange.
The Ministry of
Industry of the Republic of Indonesia targets manufacturing companies to
contribute 40 percent of GDP in the next few years of the Ministry of Industry,
(2016) (Tika and Dana, 2017). Industrial sector manufacturing companies In
contributing to the national GDP in 2015 reached 18.1% with a value of
Rp2,097.71 trillion, an increase compared to 2014 which was only 17.8% with a
value of Rp1,884 trillion (Kemenprin,2015). And towards the end of 2016, In the
third quarter, the industry grew by 5.7% or higher compared to the previous quarter
which was 5.01%. The growth of the manufacturing industry in the third quarter
reached 5.7%," said Head of the Central Statistics Agency (BPS) Kecuk
Suhariyanto in a press conference at BPS Head Office, Jakarta, Tuesday
(1/11/2016). The three main industry groups with the highest growth are
pharmaceuticals, chemical medicinal products and traditional medicines with
11.26%, food with 7.70% and leather, leather goods and footwear with 7.28%.
(finance.detik.com, 2016). In conclusion, in terms of value, the manufacturing
industry is still experiencing growth caused by increasing investment, both
from new investors and business actors who are expanding.
Product development
in the manufacturing industry sector will require large funding so it must be
very careful in determining its capital structure.� Which can be measured using the Debt to
Equity Ratio which shows how much the proportion of the company's capital comes
from debt.
The phenomenon of
capital structure experienced by the increase in net profit in industrial
sector manufacturing companies recorded a positive achievement from 2013 to
2016. The Ministry of Industry continues to encourage investment and expansion
in the manufacturing sector in order to further increase national economic
growth," said Industry Minister Airlangga Hartarto". Manufacturing
companies in the subsector that experienced the highest growth achieved by the
food and beverage industry group became the largest contributors to industrial
growth, namely 33.61 percent; followed by the metal goods industry, computers,
electronic goods, optics and electrical equipment by 10.68 percent; and the
transportation equipment industry by 10.35 percent (antaranews.com, 2016). This
achievement is inseparable from the increasing sales due to the high level of
public consumption, and the increase in production activities in the
manufacturing industry sector. Being associated with increasing sales growth
requires the expansion of additional capital to finance production activities
which are also increasing. So that efforts that will continue to be made by
emphasizing the cost of loans or debt in the capital structure in the hope that
it can continue to grow, the net profit level for the following years is
expected to increase.
With the efforts made
its management is left to professional managers to improve the capital
structure and the manager must analyze and take into account the various
variables that affect it. This study uses three variables that affect the
capital structure of manufacturing companies on the Indonesian stock exchange,
namely ROA (Return On Asset), Asset Structure and Growt Oportunity.
This ratio can
benefit the company if the return on assets increases, the company's profit
increases. According to Eni and Budiyanto (2015), the greater the ROA, which
means that the more efficient the use of company assets or in other words, with
the same amount of assets, a greater profit can be generated. This measurement
will show how much net profit can be generated by the total assets of the company.
The asset structure
and the number of assets that describe the success of the company can be used
as collateral. Assets are divided into two, fixed assets and current assets.
The company's fixed assets are widely used as collateral where the greater the assets
owned, the more the assets owned will be able to maintain trust to lend
capital. Fixed assets such as land, buildings, equipment and machinery.
Meanwhile, the company's current assets tend to use debt such as cash/banks,
short-term investments, accounts receivable, and other receivables. Asset
structure plays a role by comparing total assets with fixed assets. Companies
engaged in the manufacturing sector of the industrial sector in financing their
investments use fixed assets, because industrial sector companies have a lot of
machinery and equipment to produce from raw goods to finished goods. So that it
can be used as a guarantee and the production process will continue to grow.
this will affect the capital structure. The capital structure is related to the
comparison of total debt with total equity. These two combinations are the
goals in the company to further develop and advance in its financial turnover.
Asset structure in
the enterprise Part of the company's debt capacity is covered with intangible
assets as an asset structure. Because usually what is purchased through debt is
considered the support of creditors at the time of the liquidation of the
company. The greater the number of asset structures owned by the company will
lead to an increase in the debt ratio or funding activity by using the debt
itself. The factor that causes this phenomenon is the guarantee factor. When
the amount of the company's asset structure is said to be large, it can be
ascertained that the number of assets owned is also a lot. Diamond (2017).
If the company is
predicted to have a high growth rate, sales will be high and require additional
capital which will affect the capital structure. According to Selly and Nur
(2014) Companies that have a high growth rate will face a high information gap
between managers and investors on the quality of the company's investment
projects. The existence of this information gap causes the cost of equity
capital to be greater than the cost of debt capital because from an investor's
point of view, share capital is seen as risky compared to debt.
Companies with a high
level of sales growth in the fulfillment of their capital carry out external
funding, namely by using debt in their capital structure. In the use of debt
can cause a high burden so that the company expects a large profit that can be
used to cover the company's borrowing costs. According to Rista and Bambang in
cicilia andGusti (2016) the higher the company's sales growth rate, the use of
borrowed capital (debt) will be suppressed.
The Current Ratio
shows the company's ability to indicate the company's ability to pay its
short-term liabilities using its current assets. According to Febri (2016) in
his research, companies with a high current ratio tend not to use financing from
debt. This is because companies with a high level of liquidity have large
internal funds so that companies use their internal funds more to finance the
company's investments before using their external funds.
Based on the
description above, the author is interested. to conduct a study entitled
"THE INFLUENCE OF ROA, ASSET STRUCTURE, GROWTH OPPORTUNITY, SALES GROWTH
AND CURRENT RATIO ON CAPITAL STRUCTURE EMPIRICAL STUDY OF MANUFACTURING
COMPANIES IN THE BASIC CHEMICAL AND CONSUMER GOODS INDUSTRY SECTOR ON THE IDX
2012-2015"
METHOD
The population in this study is all industrial sector manufacturing
companies that experienced an increase in the profits of companies listed on
the IDX (Indonesia Stock Exchange) for the period 2013-2016. The sample in this
study is the industrial sector of manufacturing companies listed on the
Indonesia Stock Exchange which is consistently listed on the IDX for three
consecutive years starting from the period of 2013 to the period of 2016.
The criteria used to select the sample are as follows:
a.
Industrial sector manufacturing companies that issue complete financial
statements
b.
Industrial sector manufacturing companies that issue Annual Reports using
rupiah currency.
c.
Industrial sector manufacturing companies did not experience a decline in
assets
The data used in this study are secondary roa (return on asset) data, asset
structure, growth opportunity, sales growth and current ratio from the
financial statements of manufacturing companies for the period 2013-2016. The
method of data collection carried out is in the form of financial statements
that have been collected with a population of 44 companies and published
RESULTS AND DISCUSSION
A.
Descriptive Statistics
Through the application of statistical methods, the characteristics of the
variables tested can be described to be measured by the large amount of
research sample data using the average value (mean), the lowest value
(minimum), the highest value (maximum) and the standard deviation. As the
descriptive test results obtained below.
Descriptve
Statistics
|
|
N
|
Minimun
|
Maximum
|
Mean
|
Std.
Deviation
|
|
Roa
|
84
|
,009
|
,885
|
,19804
|
,168047
|
|
Sa
|
84
|
,029
|
,784
|
,33073
|
,161420
|
|
GROWTH
|
84
|
-,813
|
5,783
|
,21204
|
,642943
|
|
Sg
|
84
|
-,462
|
1,273
|
,11583
|
,240609
|
|
Cr
|
84
|
,514
|
13,871
|
2,82082
|
2,377000
|
|
Der
|
84
|
,083
|
3,029
|
,74423
|
,484433
|
|
Valid N
(listwise)
|
84
|
|
|
|
|
a. Return On Asset (ROA) has a mean average value of 0.198 and a standard deviation of 0.168,
meaning that the standard deviation is lower than the average value in the
return on asset variable indicating the effectiveness of the company in
managing assets. When viewed from the value of the minimum value of 0.009 and
the maximum of 0.885, it shows the company's ability to generate net profit.
The variable return on assets in this study descriptively achieves the
company's performance in generating profits, reflects the effectiveness of the
company being managed and encourages the company to fund it using internal
funds so that the debt level will be smaller.
b. The Asset Structure has a mean average value of 0.330 and a standard deviation of 0.161,
meaning that the standard deviation is lower than the average value in the
asset structure variable, indicating the effectiveness of the company in
managing assets. a minimum value of 0.029 and a maximum value of 0.784, in the
asset structure variable in this study reflects a fixed asset greater than
other asset components and each company's assets can be used as collateral.
c. Growth Opportunity has a mean average value of 0.212 and a standard deviation of 0.642
meaning that the standard deviation is higher than the average value in the
growth opportunity variable indicating that the result is not good. Because the
standard deviation is a very high reflection of deviations, so that the
distribution of data shows poor representation and causes bias. The value of
the minimum growth opportunity of -0.813 and the maximum 5,783 means the
company's ability to manage assets by showing a high asset growth rate.
d. Sales Growth has a mean average value of 0.115 and a standard deviation of 0.240
meaning that the standard deviation higher than the average value in the growth
variable indicates that the results are not good. Because the standard
deviation is a very high reflection of deviations, so that the distribution of
data shows poor representation and causes bias. The minimum sales growth value
of-0.462 and the maximum of 1.273 means the company's ability to manage assets
by showing a high level of sales growth.
e. The Current Ratio has a mean average value of 2,820 and a standard deviation of 2,377,
meaning that the standard deviation lower than the average value in the current
ratio variable indicates the effectiveness of the company in maintaining
liquidity. The minimum value of 0.514 and the maximum value of 13.871, in the
current ratio variable in this study shows that the company has increased a lot
of collection of receivables and is able to maintain its liquidity by paying
off short-term obligations so that the company is said to be good at managing
its financial statements.
f.
Capital structure (DER) has a mean average value of 0.744 and a
standard deviation of 0.484, meaning that the standard deviation is lower than
the average value in the capital structure variable (DER) indicating the
effectiveness of the company. The minimum value of the capital structure (DER)
of 0.083 and the maximum of 3.029provides the company's ability to increase its
capital.
B.
Test of Classical Assumptions
The classical assumption test can analyze the
regression model well where the calculation results show a significant and
reflective relationship with the conclusion that the regression model has no
effect and is free from the assumptions of the classical assumptions tested.
The Normality Test is used to test whether in
the research regression model the disruptive or residual variables have a
normal distribution. Regression models can be analyzed well by having a normal
data distribution. It can be tested using the one sample kolmogorov-smirnov
test. To detect it is by residual significance value. If the significance of
>0.05 indicates a residual value of normal distribution or meets the
requirements of the classical assumption.
Table 2. �Kolmogorov-Smirnov
Normality Test
One-Sample
Kolmogorov-Smirnov Test
|
|
|
Unstandardized Residual
|
|
N
|
|
84
|
|
Normal Parametersa,b
|
Mean
|
0E-7
|
|
|
Std. Deviation
|
,41752110
|
|
Most Extreme Differences
|
Absolute
|
,139
|
|
|
Positive
|
,139
|
|
|
Negative
|
-,115
|
|
Kolmogorov-Smirnov Z
|
|
1,270
|
|
Asymp. Sig. (2-tailed)
|
|
,079
|
a. Test distribution is Normal.
b. Calcuated from data
Based on the
test results in table 4.2, it shows that the normal distributed residual value
with a significant value of 0.079 is greater than 0.05. This means that Ha is accepted
to prove that data analysis can continue because the residual value has been
normally distributed.
Figure 1. Normality Test Results
Source : Spss processed data (2018)
Based on the
results of testing figure 4.1 of the p-plot chart analysis above, it can be
concluded that this research analysis is normally distributed and meets the
assumption of normality because the intended data is in the form of points that
spread around the diagonal line and follow the direction of the diagonal line.
C.
Multicolonierity Test Results
A multicolonierity test is performed to test the
regression model. The regression model can be said to be good by showing that
there is no choleration between independent variables. This test uses a
variance inflation factor (VIF) value that is declared free of multicolonierity
if the VIF value is below 10 and the tolerance (t) value is above 0.1.
Table 2. Multicollinearity Test Results
Cefficientsa
|
Type
|
|
Collinearty Statistics
|
|
|
|
Tolerance
|
VIF
|
|
1
|
(Constant)
|
|
|
|
|
Roa
|
,968
|
1,033
|
|
|
Sa
|
,799
|
1,252
|
|
|
GROWTH
|
,960
|
1,042
|
|
|
Sg
|
,875
|
1,143
|
|
|
Cr
|
,801
|
1,249
|
a. Dependent Variable : DER
Source : Spss
processed data (2018)
Based on the test results in table 4.3, it
shows that the variable return on assets with a tolerance value of 0.968 and a
VIF value of 1.033, an asset structure variable with a value of 0.799 and a VIF
value of 1.252, a growth opportunity variable with a value of 0.960 and a VIF
value of 1.042, sales growth with a tolerance value of 0.875 and a VIF value of
1.143 and a current ratio with a value of 0.801 and a VIF value of 1.249then it
can be concluded that these five independent variables are not
multicollinearity because each in�
independent variables have a greater tolerance value of 0.1 and a
variance inflation factor (VIF) value of less than 10.
D.
Heteroskedasticity
Test Results
The
heteroskedsticity test was carried out by looking at the plot graph between the
predicted value of the bound variable (dependent) namely ZPRED and the residual
SRESID.
Based on the
test results figure 4.2 sees a dot pattern on the scatterplot method. It can be
concluded that heteroskedasticity does not occur in the regression model due to
the pattern of dots that spread randomly below the number 0 on the Y axis.
Table 4. Glejser Test Results
Cefficientsa
|
Type
|
|
Sig.
|
|
1
|
(Constant)
|
,040
|
|
|
Roa
|
,405
|
|
|
Sa
|
,184
|
|
|
GROWTH
|
,448
|
|
|
Sg
|
,109
|
|
|
Cr
|
,799
|
a. Dependent
Variable : AbsUt
Source :
Spss processed data (2018)
Based on the
test results in table 4.4, it shows that the results of the five independent
variables of significance greater than 0.05 It can be concluded that the
regression model does not occur heteroskedasticity.
E.
Autocoleration Test Results
The autocorrelation test is carried out using durbin-watson
testing where the model is free from autocorrelation interference if it has a
DW value located between du < DW < (4-du). The value of du is obtained
from the durbin-watson table.
Table 4. Autocoleration Test Results
Model Summaryb
|
Type
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
Durbin-Watson
|
|
1
|
,5073
|
,257
|
,210
|
,430695
|
1,918
|
a.
Predictors : (Constant), CR, ROA, GROWTH, SG, SA
b.
Dependent Variable : DER
Source : Spss processed data (2018)
Based on the tests in table 4.5, it shows that the
regression model did not autocolerate. This can be proven by the DW value of
1.918, the dU value for the sample number of 84 with 5 independent variables is
1.773 and dL is 1.5219. Data did not occur autocoleration on dU<d<4-dU,
so it was concluded that the results obtained from this study were
1.7732<1.918<2.2268 so that it can be said to be free from
autocoleration.
F.
Model Due Diligence
a)
Xsimultan regression test results (F test)
The F test was performed to determine simultaneously the influence
between independent variables on the dependent variable by comparing the
calculated f value with the table f by looking at the signification column
0.05.
Table 4. F Test Results
ANOVAa
|
Type
|
|
Sum of Squares
|
Df
|
Mean Square
|
F
|
Sig
|
|
1
|
Regression
|
5,009
|
5
|
1,002
|
5,401
|
,000b
|
|
|
Residual
|
14,469
|
78
|
,185
|
|
|
|
|
Total
|
19,478
|
83
|
|
|
|
a.
Dependent
Variable : DER
b.
Predictors :
(Constant, CR, ROA, GROWTH, SG, SA)
Source : Spss processed data (2018)
Based on the
test results in table 4.6, it shows that the value of F 5.401 with a
significance level of 0.000 is less than the required significance value of
0.05. It can be concluded that the results of this study simultaneously on
independent variables of return on assets (ROA), asset structure, growth opportunity,
sales growth and current ratio have a significant effect on the capital
structure.
b)
�Determination Coefesiencence Test Results (R2)
The determination coefficiency test is performed to illustrate how much the
independent variable affects the dependent variable.
Table 5. Determination Coefesiencence Test Results
Model Summaryb
|
Type
|
R
|
R Square
|
Adjusted R
Square
|
Std. Error
of the Estimate
|
|
1
|
,5073
|
,257
|
,210
|
,430695
|
a. Predictors : (Constant), CR, ROA, GROWTH, SG,
SA
b. Dependent Variable : DER
Source : Spss processed data (2018)
Based on the test results in table 4.7, it
shows that the amount adjusted R2 is 0.210. This indicates that the
contribution of independent variables to dependents has an influence of 21% and
by 79% is determined by other variables that were not analyzed in this study.
c) Hypothesis
Test
A hypothesis test is carried out to
find out whether the hypothesis that has been proposed is acceptable or
rejected. In other words, any decisions on variables are made through this
study.
d) Test Results
t
The t-test was performed to
determine individually the influence between the independent variables on the
dependent variables in how to compare the values of t-count and t -table by
looking at the signification of 0.05.
Table 6.
Test Results t
Coefficientsa
|
Type
|
Unstandardized
Coefficients
|
t
|
Sig.
|
|
B
|
|
|
|
1
|
(Constant)
|
,748
|
4,636
|
,000
|
|
Roa
|
,088
|
,306
|
,760
|
|
Sa
|
,689
|
2,101
|
,039
|
|
GROWTH
|
,034
|
,454
|
,651
|
|
Sg
|
-,236
|
-1,121
|
,266
|
|
Cr
|
-,081
|
-3,646
|
,000
|
a.
Dependent
Variable : DER
Source : Spss processed data (2018)
Based on the
test results in table 4.8 of the t test, it shows the influence of independent
variables on dependent variables entered into the regression model, it can be
explained as follows:
a. The return
on assets (ROA) variable partially does not affect the capital structure. This
can be addressed by knowing that the variable return on assets (ROA) has a
significant level of 0.760>0.05. The results of the regression analysis that
ROA is positively related insignificantly to DER can be concluded hypothesis
rejected.
b. On the
variable asset structure, it is partially affecting the capital structure. This
can be addressed by knowing that the asset structure variable has a significant
level of 0.039>0.05.The results of the regression analysis that SA is
significantly positively related to DER can be concluded hypothesis is
accepted.
c. In the
growth opportunity variable, partial means do not affect the capital structure.
This can be addressed by knowing that the growth opportunity variable has a
significant level of 0.651>0.05. The results of regression analysis that
GROWTH is positively related insignificantly to DER can be concluded hypothesis
rejected.
d. In the
variable sales growth, partial means, it does not affect the capital structure.
This can be addressed by knowing that the sales growth variable has a
significant level of 0.266 >0.05. The results of regression analysis that SG
is negatively related insignificantly to DER can be concluded hypothesis
rejected.
e. The current
ratio variable partially affects the capital structure. This can be addressed
by knowing that the asset structure variable has a significant level of
0.000>0.05. The results of regression analysis that CRbe is significantly
negatively related to DER can be concluded hypothesis is accepted.
e) Multiple
Linear Regression Analysis Test Results
Multiple linear regression tests
were carried out to determine the direction and magnitude of the influence of
independent variables on dependents on industrial sector manufacturing
companies on the Indonesian stock exchange in 2013-2016. The results of the
multiple linear regression test can be seen in table 4.9.
Table 4. Multiple Linear
Regression Analysis Test Results
Coefficientsa
|
Type
|
Unstandardized
Coefficients
|
Standardozed
Coefficients
|
|
B
|
Std. Error
|
Beta
|
|
1
|
(Constant)
|
,748
|
,161
|
|
|
Roa
|
,088
|
,286
|
,030
|
|
Sa
|
,689
|
,328
|
,229
|
|
GROWTH
|
,034
|
,075
|
,045
|
|
Sg
|
-,236
|
,210
|
-,117
|
|
Cr
|
-,081
|
,022
|
-,398
|
a.
Dependent
Variable : DER
Source : Spss processed data (2018)
Based on the test results in table 4.9 of the multiple
linear regression analysis test for this study, DER = 0.748 + 0.088 ROA + 0.689
SA + 0.034 GROWTH � 0.236 SG� 0.081 CR from the regression coefficient equation
above can be explained as follows:
a. The results
of the research from the regression model are known to be a constant of 0.748
which means that if the value of the independent variable (return on assets,
asset structure, growth opportunity, sales growth and current ratio) is zero,
then the dependent variable (capital structure) is 0.748.
b. The results
of the study from the regression model for return on assets are known to be
0.088. The value of the return on assets generated positively shows that there
is a relationship that is in the same direction as the capital structure which
means that any increase in return on assets by 1% will increase the capital
structure by 0.088 assuming other independent variables are constant.
c. The results
of the study from the regression model for the asset structure are known to be
0.689. The value of the asset structure generated positively indicates a
relationship that is in the same direction as the capital structure which means
that any increase in the asset structure by 1% will increase the capital
structure by 0.689 assuming other independent variables are constant.
d. The results
of the study from the regression model for growth opportunity are known to be
0.034. The positive growth opportunity value shows a relationship that is in
the same direction as the capital structure, which means that every increase in
growth opportunity by 1% will increase the capital structure by.
e. The results
of the research from the regression model for sales growth are known to be
-0.236. The resulting sales growth value negatively indicates a decrease in the
capital structure which means that any increase in growth by 1% will reduce the
capital structure by -0.236 assuming other independent variables are constant.
f. The results
of the study from the regression model for the current ratio are known to be
-0.081. The resulting negative current ratio value indicates a decrease in the
capital structure which means that every increase in the Current Ratio by 1%
will reduce the capital structure by -0.081 assuming that other independent variables
are constant.
f)
Effect of
Return On Assets On Capital Structure
Based on the
test results of statistical analysis it was found that the H1 hypothesis was
rejected. So it can be concluded that the return on assets does not affect the
capital structure with a significant value of 0.760 >0.05 The results of
this study do not support Riski (2015) andIntan (2014) but on the contrary
support research from Febri (2016).
The results
of this study show that increasing or decreasing return on assets does not affect
the capital structure. In this case, the company prioritizes the amount of
sacrifice and the profit it has. As the amount of benefits obtained from
sacrifices arising from the use of company capital to support the company's
operations. And don't look at the small amount of return on assets. This is
because industrial sector manufacturing companies have assets that can be used
for the company's operational activities, so that they can use existing assets,
as long as the company is still running normally and has profits. With the
conclusion that the increase or decrease in return on assets does not affect
the capital structure. Judging from the ability of manufacturing companies in
the industrial sector to always increase and generate profits because consumer
factors always believe in the products produced without the need for capital
increase expansion.
g)
Effect of
Asset Structure on Capital Structure
Based on the
test results of statistical analysis it was found that the H2 hypothesis was
accepted. So it can be concluded that the asset structure affects the capital
structure with a significant value of 0.039 <0.05 The results of this study
do not support Mukhlan (2016) and Selly (2014) but instead support research
from Novione and Rusmala (2016).
The results
of this study show that when the asset structure experiences an increase, the
company's capital structure increases. This happens because the asset structure
is measured by the amount of fixed assets that can be used as collateral by
indicating that a large number of assets will be able to maintain investor
confidence to lend capital as a guarantee of the company's ability to pay off
debts. Regarding guarantees, the company in establishing the capital structure
by increasing the amount of income so that it is able to increase assets.
According to Selly and Nur (2014) in harjati and eduardus (2007) the higher the
fixed assets owned, the company also has a guarantee of greater ability to
carry out external funding which means it has the potential to improve capital
structure.
h)
The Effect
of Growth Opportunityon Capital
Structure
Based on the
results of statistical analysis testing for this study, it was found that the
H3 hypothesis was rejected. So it can be concluded that growth opportunity does
not have a significant effect on the capital structure with a significant value
of 0.651<0.05 The results of this study support Tika and Dana (2017)
The results
of this study show that when growth opportunities experience an increase or
decrease, it does not affect the capital structure. This is because the company
prioritizes the company's performance and generates profits, the profit comes
from asset growth where the results of asset growth can increase the company's
profit. according to Arief (2016) companies that have a high growth rate tend
to be more willing to hold their profits to finance growth than to divide it as
dividends. The highest growth is owned by three industry groups, namely
pharmaceuticals, food and beverages and cosmetic goods.� Indicating that the future growth opportunity
will be more developed so that the company knows the growth rate of the company
generated from profits in the company to fund its growth.
i)
The Effect
of Sales Growthon Capital Structure
Based on the
results of statistical analysis testing for this study, it was found that the
H4 hypothesis was rejected. So it can be concluded that Sales Growth does not
affect the capital structure with a significant value of 0.266<0.05. The
results of this study support Nudzunul andSuwitho (2015).
The results
of this study show that increasing or decreasing sales growth does not affect
the capital structure. This is because the company's growth rate uses more
profit from the sales proceeds obtained to re-finance production activities so
as to generate profits. According to Edwarddkk (2010) companies can develop
product sales using the total quality management method where management
assures that the company's products and services can exceed customer
expectations, useful for measuring quality aspects of product sales. So there
is no need to use debt because the profit obtained will increase. This is due
to the increasing and growing sales of products. However, this result is not in
accordance with the research of Cicilia and Gusti (2016) which states that the
faster the growth rate of the company's sales, the more it will increase
financing with debt.
j)
Effect of
Curren Ratio on Capital Structure
Based on the
results of statistical analysis testing for this study it was found that the H5
hypothesis was accepted. So it can be concluded that the Curren Ratio has an
effect on the capital structure with a significant value of 0.000<0.05.
These results do not support the research of Arief et al (2016), Riski and
Suwitho.
The results
of this study show that the current ratio increases further decreases the
company's capital structure, this is due to the company's current assets
increasing and the company can cover short-term liabilities using current
assets. So that companies use less debt. Stephen et al (2014) this is in
accordance with the theory of pecking Order is one of the alternatives for
companies to choose to use funding from within the company (internal) namely
current assets. If a company has a large profit, the company may never need
funding from outside the company (external). So the company will probably have
a little debt.
This
research in accordance with Febri (2016) states that companies with a high
current ratio have funds from within large companies. So that the company does
not use additional capital from debt, but rather uses its internal funds to
finance investments
CONCLUSION
This study aims to determine the effect of return on assets, asset
structure, growth opportunity, sales growth and current ratio on capital
structure. Based on the results of regression model testing that has been
carried out with 84 samples used in the research period from 2013 to 2016, the
following conclusions can be drawn: Return on assets has no effect on the
company's capital structure. So it is concluded that increasing or decreasing
on assets does not affect the capital structure. This is because the company
prioritizes the amount of sacrifice and has the advantage of supporting the
company's operations, by not looking at the small size of the return on assets.
The asset structure positively affects the company's capital structure. With
the conclusion that the increasing asset structure, the company's capital
structure is increasing. This happens because the asset structure is measured
by the size of fixed assets, so that the amount of fixed assets can be used as
collateral for additional funds or capital using debt so that it can provide
confidence to investors that the company is able to pay off its debts. Growth
opportunity does not affect the company's capital structure. So it is concluded
that when the growth opportunity increases or decreases, it does not affect the
capital structure. This is because the company prioritizes company performance
and generates profits derived from asset growth that can increase production
activities and encourage company performance to be able to generate profits that
are produced. Sales growth does not affect the company's capital structure. So
it is concluded that when sales growth increases or decreases, it does not
affect the capital structure. This is because the company uses the company's
profits more to finance its production activities so that it can generate
profits that can be used as company capital. Current ratio negatively affects
the company's capital structure. This means that the more current assets
increase, the lower the capital structure, this is due to the current ratio
using current assets more for company funding. because the company's current
assets increased the company used receivables and inventories to be able to pay
its short-term liabilities first to collect receivables and sell inventory to
be cashed to pay current liabilities.
REFERENCES
Augustine, K. (2016). The influence of managerial ownership structure,
asset structure, liquidity, business risk, dividend policy, firm size, and
restaurant and tourism industries. Journal Of Business Research.
Arief, I. T. (2016). Effect of Firm Size, Growth Opportunity,
Profitability, Bussiness Risk, Effective Tax Rate, Asset Tangibility, Firm Age
and Liquidity on Company Capital Structure (Study on Property and Real Estate
Sector Companies Listed on the IDX in 2009. Journal of Business Administration.
Cicilia, K. (2016). The Effect Of Profitability, Investment Opportunity
Sets, Sales Growth, And Business Risk On Capital Structure. E-Journal of
Accounting Udayana University , Vol 14.
Edward J.B., D. E. (2011). Cost Management, Strategic Emphasis.
Febri, W. (2016). Effect of Asset Growth, Current Ratio, Return On Assets
Business Risk And Tax Savings On Capital Structure In Manufacturing Companies
In The Consumer Goods Industry Sector. King's Maritime University thesis.
Friska, F. (2011). Factors Affecting the Capital Structure of Manufacturing
Companies on the Indonesia Stock Exchange. Journal of Business And Accounting .
I God A.N & Niputu, A. (2016). The Effect Of Company Size And
Profitability On Company Value With Capital Structure As A Moderation Variable.
Priest, G. (2013). Spss 23. 93-158.
Jean, J. (2004). Determinants Of Capital Structure Of Chinese-listed
Companies. Journal Of Business .
Khuzaini, &. Nanto. (2014). The Effect Of Liquidity And Profitability
On Capital Structure And Activity Ratio As Intervening.Journal Of Business And
Accounting
Kiki, E. & Fidiana. (2016). The Effect of Growth Opportunity,
Profitability and Asset Structure on Capital Structure. Journal of Accounting
Science and Research .
Mohammad, A. d. (2015). Determinants of capital structure: an empirical
study of firms in Iran. Journal Of Law and Management .
Mukhlan, K. & Meina. (2016). Factors Affecting Capital Structure (Case
study on Manufacturing Company listed on the Indonesia Stock Exchange for the
Period 2011 � 2014). Journal of Management Insights .
Ni Kadek T.S.D & Imade, D. (2017). Effect of Growth Opportunity,
Liquidity, Non-Debt Tax Shield And Fixed Assets On Capital Structure. E-Journal
of Management of Udayana University .
Ni Made, N. & Made R. (2016). Effect of Sales Growth, Asset Structure
and Asset Growth on Capital Structure. E-Journal of Management Unud , Vol 5.
Niputu, M. L. (2016). Effect Of Profitability And Asset Growth On Corporate
Governance And Capital Structure. E-Journal of Economics and Business Udayana
University , 4366-4367.
Nirosha H.W & Stuart, L. (2014). Impact Of Ownership Structure On
Capital Structure Of New Zealand Unlisted Firm.
Nur, I. (2014). The Effect of Asset Structure, Growth and Profitability on
Capital Structure in Companies Listed on the Indonesia Stock Exchange. Thesis
of The University of Negri Padang.
R, Zeitun. & G.G, Tian. (2007). Capital structure and corporate
performance: evidence from Jordan. Australasian Accounting Business And Finance
.
Riski, D. (2015). The Effect of Liquidity, Profitability on the Capital
Structure of Automotive Companies Listed on the IDX. Journal of Accounting
Science And Research .
Selly, Z. & Nur. (2014). Effect of Profitability, Asset Structure and
Growth Rate on Capital Structure. Journal of Accounting Science And Research .
Stephen, A.R. Introduction to Corporate Finance. 107-112
Sitanggang. (2015). Advanced Corporate Financial Management. 27-30.
Siti, H. & Barbara. (2010). Effect of Liquidity Size, Risk
Profitability and Sales Growth on Capital Structure. Journal of Accounting and
Investment , vol 11.
Sugiarto. (2009). Capital Structure of Company Ownership Structure, Agency
And Information Asymmetry issues, 2,3,54-58.
Toto, P. (2013). Capital Budgeting and Fixed Asset Management.Introduction
to Corporate Finance. 473-480
http://industri.bisnis.com/read/20160222/257/521557/pdb-2015-sektor-manufaktur-berkontribusi-181.
http://www.kemenperin.go.id/artikel/14532/Kontribusi-Industri-Manufaktur-Melesat.
http://www.kemenperin.go.id/artikel/7014/Manufaktur-Ditopang-Sektor-Barang-Konsumsi.
https://finance.detik.com/bursa-dan-valas/d-3571364/perjalanan-induk-usaha-pt-ibu-di-bursa-hingga-kesandung-kasus-beras.
https://finance.detik.com/bursa-valas/3446186/penjahit-hm-dan-guess-ini-raih-laba-rp-790-miliar-di-2016.
https://finance.detik.com/bursa-valas/3668022/catatkan-saham-perusahaan-tekstil-ini-dapat-dana-segar-rp-45-m.
https://finance.detik.com/industri/d-3799609/industri-manufaktur-sumbang-22-pdb-ri.
https://www.antaranews.com/berita/410846/pertumbuhan-industri-nonmigas-2013-capai-622-persen.
www.idx.co.id.
Received: 03-08-2022������������������������������������ Accepted: 14-08-2022�������������������������������������� Published:
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