Operating Activities Cash Flow Effect on The Performance Of The Market (Study In Industrial Goods Manufacturing Sector Consumption Listed in BEI 2016-2017)
Dewi cahyani Syaputri STIE Widya Gama Lumajang noecahyani@gmail.com
Abstract
This study attempts to give empirical evidence: about 1.) The influence of cash flow operations on market performance, 2. ) A company that has higher performance growing niche market to influence the cash flow .The research is a service enrolled in bii for 2 years (2016-2017) the company about 43 consumer goods. Engineering samples in use is the purpose of sampling .Analysis assistance programs the data using SPSS 19.0 for windows consisting of three types of analysis, the analysis, multiple regression, and analysis of the different t-test .The result of this research suggests that cash flow operations will not Affect market performance, this PROVE that it is not all companies show high profits on financial reports that look good financial performance. There are some of the companies that in fact have a high profit,
Keywords: cash flow operations, market performance
INTRODUCTION
Capital markets are exchanges that are the means to bring the bidder and permintaan.Perusahaan have a lot of contract work for example konrak between the company and its managers and the loan contract between the company and the manager ith the loan contract between the company and its creditors (Scott, 2000).
Capital market also requires information on a company's financial statements to make investment decisions in perusahaan.Salah one component of the financial statements into consideration for an investor to make decisions.
According Roychodhuri: 2006 report operating cash flow into a report which is very important for an investor, because under normal circumstances scale of total assets would seem there is no manipulation of the activity of the real, and if the report operating cash flow is low or normal scale of total assets is low then it would seem there is manipulation The real activity through operating cash flow.
So that one indicator of the good performance of a company is to achieve a profit. "Profit is a summary of the results of the business operating activities expressed in financial terms" (Wild et al, 2008: 408).
Manager as manager of the company more aware of internal information and the company's prospects in the future aka Dating in appeal owners or
shareholders, because managers have direct contact with the entity or company and knowledge of a
Scoot (2000), there are two kinds of asymmetry informai that is adverse selection and moral hazard.Adverce selection information related to the imbalance between the manager and the user, so the fact that may influence the decision of the shareholders. Moral hazard.berkait with the activities carried out by seirang manager is not entirely known by shareholders and providers pinjama. so the manager can perform actions outside the knowledge of the holder of information and conflicts of interest saham.Asimetri encourage agents to present information to the principal yangtidak seenarnya, especially if the information relates to the performance of agents (Widyaningdyah, 2001).
Herawaty (2008) explains that one form of irregularities committed by the management as an agent in the process of preparing the financial statements that management can affect the rate of profit yan shown dalamlaporan financial or often called management earnings, management, profit occurs when managers use judgment in financial reporting and preparation of transactions that can change the financial statements that mislead the parties concerned with the Vendor. (Healy and Wahlen, 1999).
Profit management is generally done in two ways: accrual manipulation and manipulation of real activity. Manager like the real activity manipulation techniques compared to earnings management through accrual (Graham et al., 2005)
Roychowdhury (2006) explains that the earnings management dapatdilakukan with pure accrual earnings management and real earnings management or manipulation activities riil.Manajemen pure accrual earnings (pure accrual) accrual.Discretionary discretionary accruals made through so-called earnings management akrual.Manajemen accrual earnings at the end of period when the manager knows profitability before engineered so that it can determine how much manipulation necessary for profitability targets tercapai.Sedangkan real earnings management (real activities manipulation or manipulation of real activity) can occur throughout the accounting period. Real earnings management activities starting from the normal operational practices,
According Murhadi, 2009). There are two things that underlie chosen profit management through real activities, namely:
1. Manipulation more often dijaikan center accrual observation or inspection by auditors 2. Only focusing on a manipulation of accruals is a risky action.
This affects the manager to shift from accruals to manipulate the activity of sales riil.Managemen trying to increase sales during the accounting period the aim of increasing profits in order to profit targets are met. The next technique is to conduct a large scale production (overproduktion), producing goods greater than that required aim to achieve the expected demand so that profits increased. Profit growth continues to increase from year to year gives a positive signal about the prospects for the company in the future. Theoretically, companies that obtain high profits will be able to distribute dividends semaki great and positive influence on stock returns. In the eyes of investors and potential investors this is an appeal to invest by buying shares of the company resulting in increased demand for stocks. If the demand for shares increases show that the better performance of the market, because the level of investment pengemalian (return) long-term corporate or stock returns are a measure of the performance of the enterprise market.
METHOD
This research uses descriptive method kuanitatif. According to Sanusi (2011: 115-116) descriptive method is a method which is used to analyze the data in ways that describe or depict the data collected as without meaning. to make general conclusions or generalizations apply. This study was included in the category of qualitative research because research data research that explains the quality of sosialn influence which is not illustrated through a quantitative approach (Saryono, 2010: 1)
Descriptive research conducted to describe a phenomenon, events, and the events that occurred factual, systematic and accurate. Quantitative descriptive research is research conducted to determine the value of a variable or more (independent) without making comparisons or connect with other variables.
RESULTS AND DISCUSSION
History of Indonesia Stock Exchange which was established by the Dutch in Indonesia precisely in 1912 in Batavia. The Jakarta Stock Exchange, in ancient times a little bit disturbed arrangement because at that time Indonesia was still at war, and eventually was closed. In the end, the Jakarta Stock Exchange re-opened in 1977 under the supervision of Bapepam. On July 13, 1922, the Jakarta Stock Exchange was privatized by the establishment of the Jakarta Stock PT.Bursa. This is where it started actively back the Jakarta Stock Exchange .In 1995 trade electronic trading on the Jakarta Stock Exchange ended at the start
In 2007 the Jakarta Stock Exchange and Surabaya Stock Exchange experienced a merger process that eventually renamed .Mengakibatkan Indonesia Stock Exchange has a market capital Jakarta centralized .Bursa effect can be used while the stock market as the Surabaya Stock Exchange and oblogasi derivative markets.
Manufacturing companies is the company that runs the manufacturing process. A company can say if there is a manufacturing company input output process that ultimately results in products. Of the 153 companies that become the population, there are 43 manufacturing companies that meet the criteria of sampling. For further dpat process is carried out further analysis in this study. There are 21 companies such as shown in the following table:
No. Company name Company code
1 Akasha Wira Internatioal Tbk ADES
2 Polychem Indonesia Tbk ADMG
3 Tiga Pilar Sejahtera Food Tbk AISA
4 Argha Karya Prima Industry Tbk AKPI
5 Chitose International Tbk CINT
6 Light Wilmar Indonesia Tbk. CEKA
7 Delta Djakarta Tbk DLTA
8 Gudang Garam Tbk GGRM
9 Indofarma Tbk INAF
10 Indofood Sukses Makmur Tbk INDF
11 Kimia Farma Tbk KAEF
13 Multi Bintang Indonesia Tbk MLBI
14 Mayora Indah Tbk MYOR
15 Mustika Ratu Tbk MRAT
16 International Bentoel Investama RMBA
17 Medicine Industry And Famasi Sido Appears Tbk SIDO
18 Unilever Indonesia Tbk UNVR
19 Ultra Jaya Milk Industry Tbk ULTJ
20 Wismilak Inti Makmur Tbk WIIM
21 Wijaya Karya Tbk WIKA
Sumbber: IDX
Cash flow (cash flow) is a financial statement containing the influence of operating cash, investment transaction activity and transaction activity financing / funding and the net increase or decrease in cash of a company during the period.
Operating cash flow operating activities generate revenues and expenses from principal operations an operation perusahaan.Aktivitas affect the income statement, reported by akrual.Sedangkan basic cash flow statement reports cash impact on incoming kas.Arus opersi biggest cash came from the collection of subscriptions. cash inflows less important is the receipt of interest on loans and dividends on investment saham.Arus out of operating cash include payments to suppliers and employees, as well as interest payments and taxes.
Market performance is a measure of company performance as measured by the rate of return on the company's long-term investment or stock returns .Komponen cash flow from operations and financing activities linked to the return. The rate of return is expected to be the market price determined and adjusted to a desired rate of return for investors .For investors, expected rate of return equal to the expected rate them, therefore they are willing to pay the market price which now applies to securities the. data on market performance ratio is taken from the financial statements of companies listed on the Stock Exchange.
Here are the results of calculation of descriptive statistics of all variables in this study, Table 4.5 Results Calculation Deskriptive Statistics
descriptive Statistics
N Minimum maximum mean Std. deviation
Cash flow 42 -.95 26.86 .7862 4.17703
Market performance
42 -18.49 2.2410 5.32358 3.450029 Valid N (listwise) 42
Based on Table 4.5 it can be seen that:
a. Cash flow has an average of 0.7862 and a standard deviation of 4.17703, which means that most of the cash flow is worth 0.7862 with the irregularities in approximately less than 4.17703 or above 0.7862.
b. Value sized companies have an average of 5.32358 and a standard deviation of 3.450029, which means that size is worth 5.32358 perisahaan with deviations around less than 0.2037 or more than 3.450029
The aim was to determine the normality test in the regression model, or residual confounding variables have a normal distribution. To determine the normal symptoms can be determined using the graph on the condition that if the data spread around the diagonal line and follow the direction of the diagonal line then the data meet the assumption of normality. The method used in this study is a sample of the Kolmogorov-Smirnov test to test normal distribution where the criteria used are: If significant Asymp.Sig. (2-tailed) greater dari0,05 then the data is normally distributed
Table 4.6 One-Kolmogorov Smirnov
Source: SPSS output (data processing), 2019
Multicolinearity test aims to test whether the regression model found a correlation (correlation) between the independent variables. A good regression model should not happen multikolinearitas.
Multikolinearitas, can be seen from the value of tolerance under 10 and the amount of Value Inflation Factor (VIF). If the value of VIF> 10 that there is multicollinearity, otherwise if VIF <10 then there is no multicollinearity. The following test results multikolinearitas
Table 4.7 Coefficient collinearity Diagnosticsa
tolerance VIF Information
Cash flows Operating
activities 1,000 02 Did not happen
multicolinearity Market performance
7.213 98 Did not happen
multicolinearity Source: SPSS output (data processing), 2019
Sample Kolmogorov-Smirnov Test Residual unstandardized
N 42
Kolmogorov-Smirnov Z 3,299
Asymp. Sig. (2-tailed) 000
From the above table shows using the Kolmogorov-smirnovmenunjukan that the data is distributed normal.Hal residuals can be seen in the column Asymp. Sig. (2-tailed), which showed a value of 3299 greater than 0.05, so that (data) residuals are normally distributed.
Based on Table 4.7 it can be concluded that these two variables have a tolerance value <0.10 so that it can be concluded that there is no multicollinearity and VIF <10 so that it can be concluded that there is no multikolinearitas
Heteroskedasitas test aims to test whether the regression model equation is happening ketidakk residual variance from one observation to another observation that the interpretation of the regression coefficients become the coefficients and interpretation of the results will be less accurate. A good regression model is that Homoskedastisitas or not happen Heteroskidastity.
The means used to prove that there is no heteroscedasticity is through graphs Scatter Plot on the condition that there is no clear pattern, as well as the points spread above and below the number 0 on the Y axis, then there is no heteroscedasticity. Based upon the above test results show that the distribution of points to form a pattern means there heteroskedastisitas.
Autocorrelation aims to test whether the linear regression model was no correlation between bullies error in period t with bullies error in period t-1 (previous). Yangn good regression model is a regression that is free of autocorrelation. Knowing the autokolerasi can use the Durbin-Watson test (DW test) provisions do not occur autokolerasi, if the value of DW is between -2 and +2 or (-2 <DW <+2
Table 4.9 Model Summaryb
Based on Table 4.9 it can be concluded that the value of DW amounted to 1,998. It can be seen from the table Durbin-Waatson value DL = 1.4073 and DU = 1.6061 so that the conclusions from the detection of positive autokolerasi is DW> DU it can be stated that there is no autokolerasi positive and negative conclusions from autokolerasi detection is (4-DW)> DU it can be stated that there is no negative autokolerasi. So can disimpulkann on autokolerasi regression analysis there are positive and negative autokolerasi so that it can be concluded not happen autokolerasi.
Analysis of the data for this research hypothesis testing using multiple linear regression model (Multiple Linear Regression). Intended use multiple linear analysis was to test the effect of two or more independent variables / independent (Cash Flow Operations) on the dependent variable / dependent (KINERA Market) which are known from the regression equation. This test was performed using SPSS (Statistical Package for Social Science) version 21 for Windows. This regression model is used in order to test the hypothesis formulated in the study following the results of multiple regression analysis.
Table 4.10 Results of Multiple Regression Analysis
Model
Coefficients unstandardized
standardized Coefficients
t Sig.
B Std.
Error beta
1 (Constant) 6,712 , 486 13.7
99 , 000
Model Durbin-Watson
1 1,998
Operating cash
flow to , 076 , 070 -070 -
1088 1,000 Market
performance
Source: SPSS output (data processing) 2019
According to the table can be seen 4:10 regression equation used in this study are:
DACit = 6.712 to 0.76) UP + 1.584 P + ε
The coefficient of determination (R2) can be used to measure the ability of independent variables explain the dependent variable. Coefficient of determination is between 0 and 1. The value of R2 is small means that the ability of independent variables in explaining the variation. The independent variable is very limited (Ghozali, 2005). If the coefficient of determination is very close to 1, then the independent variables will have an effect on the dependent variable
Table 4.11 Coefficient Determination Test Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of the Estimate
1 .170a .029 .004 .85758
Source: Data processed in SPSS, 2019
From the table above it can be seen that the adjusted R2 is equal to -0.04 or 0.4%. This shows that earnings management variables can be explained by the size and profitability of 0.4%. While the remaining 99.6% is explained by other factors outside the model analysis.
Standard Error of the Estimate(SEE) is 0.85758, the small value shows that the regression model can accurately predict the dependent variable, which is where the smaller SEE the regression model would be more accurate in predicting the dependent variable.
F statistical test used to determine whether the independent variables included in the regression models have influence together (simultaneously) on the dependent variable (Ghozali, 2005). If the significance probability value <0.05, it is clear that the independent variable can jointly affect the dependent variable.
Test Results Table 4.12 F
Model Sum of
Squares
df mean Square F Sig.
1
Regression , 462 2 , 231 , 841 , 439b
residual 10.724 39 , 275
Total 11,187 41
Based on Table 4:12 shows that this equation model has a significance level of 0.439 greater than 0.05 alpha. This shows that the independent variable firm size and profitability is not significant on the dependent variable earnings management.
To test the hypothesis partially it will use statistical tests t that can be used to determine how far the influence of the independent variables individually in explaining the variation of the dependent variable (Ghozali, 2005). If the significance probability value <0.05 then this is an independent variable is a significant explanatory against the dependent variable.
Test Results Table 4.13 T
Under the table 4:13 can be concluded that the two independent variables
t variables Sig Information
13 799 Operating cash flow .000 Not significant -1088 market performance .283 Significant Source: SPSS output (data processing), 2019
As for the influence or the hypothesis of each explanatory variable / independent of the dependent variable in this study are described as follows:
Hypothesis testing 1 shows that the accounts receivable turnover positifterhadap affect liquidity. This is shown in the table above that the regression coefficient test variable operating cash flow amounted 0,00nilai showed sig is smaller than α = 0.05, which indicates variable operating cash flow is negatively and significantly influence market performance.
Testing the hypothesis 2 shows that the cash turnover significant negative effect on liquidity. This is shown in the table test multiple linear regression coefficients for the variables above that the market performance showed sig of 0.283 is greater than the value of α = 0.05, which shows the wear variable partial cash opersi has a positive relationship and influence on market performance
CONCLUSION
In this study for mengujiperputaran receivables and cash turnover on the liquidity of the industrial sector manufacturing companies listed on the Stock Exchange of goods konsumsiyang years 2016- 2017. The number of samples obtained 21 with a population of 43 annual reports.
Based on the results of research and discussion conducted, it can be summed up as follows:
1. Operating Cash Flow positive effect on market performance. This is shown in the table above that the regression coefficient test variable operating cash flow showed a sig equal to 0,462 this value is greater than α = 0.05, which shows the operating cash flow variables have a positive relationship and no significant effect on the performance of the market.
2. Cash Flows Operating activities significant negative effect on the performance of the market. This is shown in the table test multiple linear regression coefficients for the variables above that shows the operating cash flow amounted to 0.076 sig smaller this value of α = 0.05, which shows the cash flow variable partial operations have a negative relationship and affect the performance of the market.
3. Based on t test results can be concluded that the hypothesis is acceptable with numbers less significance of α = 5%. T test results showed the effect of variable cash flows operating activities on the performance of the market with determination coefficient of 0.283
4. Variable Cash Flows Operating activities showed no significant effect on the performance of the market value on the company's manufacturing companies listed in Indonesia Stock Exchange from 2016 to 2017.
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