Identification of Financial Distress With Company Size As A Moderating Variables in Southeast Asia Property and Real Estate Industry

. The objective of this study is to investigate the simultaneous and partial effects between the variables net profit magin, current ratio, and debt to asset ratio to financial distress as moderated by the Firm Size variable in property and real estate companies listed on the Southeast Asia Stock Exchange 2012-2019. Sampling technique used in this study is purposive sampling technique. Sample in this study were 35 companies within 8 years. Therefore, a total of 280 company samples were obtained. technique of analysis used in this study is multiple regression and MRA (Moderated Regression Analysis) using the SPSS 21.0 application. Based on the results of the study, the variable net profit magin, current ratio, and debt to asset ratio affected financial distress by 53.4%, and the remaining 46.6% was influenced by other factors outside the research variables. Partially, the variable net profit margin, current ratio, debt to asset ratio partially has a significant effect on financial distress. Meanwhile, the firm size moderation model does not moderate net profit margin, current ratio, debt to asset ratio to financial distress.


INTRODUCTION
The spread of the COVID-9 corona virus has paralyzed many sectors and joints of the world's economies, including developing countries in the Southeast Asia region. The property and real estate sub-sector is one of the subsectors that is quite affected by the COVID-19 virus. Property and real estate are businesses engaged in the ownership of assets, both in the form of residential buildings and buildings for commercial purposes. The property and real estate business can provide high and promising profit prospects so that competition between companies both inside and outside the country is very competitive. The property and real estate subsectors have a significant influence in reviving the economy in Southeast Asia, but on the other hand, the value of corporate financial distress in this sub-sector has a fluctuating value due to the ups and downs of the company's financial statement data. Analyzing financial distress and financial reports can be used to assess the performance and soundness of the company, and also to evaluate the effectiveness of policies taken by management. Source: Data is processed from several sources of stock exchanges in Southeast Asia using Microsoft Excel (2016) Figure 1 shows the results of the analysis of the lowest level of financial risk in Thailand in Southeast Asia, namely 2019, while the highest level of financial risk in Thailand is also in 2015. Based on the Z -Score> 2.99 criteria, namely the level of safe risk and the The level of risk for a vulnerable position is based on the Z-Score 1.81 <Z <2.99 criteria, while the distress risk level is based on the Z-Score <1.81 criteria. The high and low value of the company's financial distress shows the company's financial health and the performance of management policies in managing funds. The small financial distress value of the company, the less likely the company will go bankrupt.
In making decisions to invest, in addition to looking at the level of the company's financial risk, investors also look at the company's financial ratios such as profitability ratios. Profitability ratio analysis is used to measure the company's ability to carry out investment activities, and also to measure the company's success in obtaining acceptable profits.
Profitability ratios consist of, NPM (Net Profit Margin), ROI (Return On Investment), ROA (Return On Asset), and ROE (Return On Equity). The profitability ratio used in this study is NPM (Net Profit Margin). NPM (Net Profit Margin) shows the efficiency of management performance in managing the company and also shows the percentage of the company's net profit to net sales which is used by the company to pay company costs and to find out what percentage of profit will be distributed to shareholders. Margin) ratio shows that the company's overall ability to generate net profit and dividend payments to shareholders or profits which will be reinvested into the company.
The liquidity ratio that will be used in this research is CR (Current Ratio). The value of CR (Current Ratio) describes the company's ability to pay short-term debt using current assets. Singapore. The high and low value of the current ratio shows the liquidity of the company in its ability to pay its short-term debt obligations. This ratio is used by prospective creditors to determine whether or not to provide short-term loans to companies. In addition to analyzing liquidity ratios, analyzing leverage ratios is also necessary to determine financial difficulties experienced by a company.
Through the leverage ratio, the financing used in carrying out the company's operational activities can be identified, whether from debt or from equity. The leverage ratio used in this study is DAR (Debt to Asset). The value of DAR (Debt to Asset) describes a company's ability to pay its long-term debt.  Figure 4 shows the lowest Debt Asset Ratio indicator value in Thailand in Southeast Asia, namely in 2017, while the highest DAR value was in 2014 in Thailand as well. The value of the DAR ratio shows how much the company's assets can pay off the company's debt. The higher the DAR value, the higher the company's risk level in paying off its obligations Total company assets, both current assets and fixed assets, can describe the size of a company. The greater the total assets owned by the company, the easier it will be for management to use the assets in the company, so that the company's value will be better. Source: Data is processed from several sources of stock exchanges in Southeast Asia using Microsoft Excel (2016) Figure 5 shows the lowest Firm Size Indicator value in the Sinagpura country in Southeast Asia, namely in 2014, while the highest firm size value is in the Philippines in 2019. The high or low firm size value shows the size of the total assets owned by the company.
According to results of previous research Debt to Assets Ratio (DAR) dan Current Ratio (CR) have a significant on financial distress [1]. The current ratio, total debt to total capital asset ratio, and firm size have a significant effect on financial distress [2]. The current ratio and net profit margin have a positive effect on financial distress [3]. The current ratio has a positive effect on financial distress [4]. The debt to total capital asset ratio has a positive effect on financial distress [5]. The total debt to total capital asset ratio has a positive effect on financial distress [6]. The current ratio has a positive effect on financial distress [7]. The debt to total capital asset ratio and current ratio have a positive effect on financial distress [8]. Firm size has no significant effect on financial distress [9].
Based on the description above, researchers are interested in conducting research with the title "The Effect of Net Profit Margin, Current Ratio, and Total Debt To Total Capital Asset Ratio Against Financial Distress with Firm Size as a Moderating Variable (Empirical Study of Property and Real Estate Subsector Companies Listed in Southeast Asia Stock Exchange 2012-2019) ".

Financial Risk
Risk can be interpreted as a form of uncertainty about a situation that will occur later (future) with decisions taken based on various considerations at this time [10]. To determine the level of financial risk or financial distressed, companies can predict the potential for bankruptcy with the Altman Z-Score method. The Altman Zscore method is an analytical model that functions to predict company bankruptcy with relatively reliable accuracy, so this analysis can be used to regulate the financial risk level of a company. Financial risk analysis is an important tool for obtaining information relating to financial position with the results that have been achieved through the selection of corporate strategies that will be applied [11].
In assessing the level of financial risk required data and financial statements consisting of income statements and balance sheets. After each data is obtained, then analyzed using the Z-Score method, the company allows to know whether it has a low level of risk, is in a vulnerable position, or has a high level of risk. To be able to analyze the financial risks previously processed data processing by calculating, as for the formula that can be calculated as follows:

Working Capital to Total Aset
Intended here is an analysis between current assets with current debts (Current Liabilites) Working Capital to Total Aset = Working Capital/Total Assets

Retained Earning to Total Aset
Retained here is retained earnings, retained earnings to total assets is the company's ability to generate profits in a certain period in terms of the company's ability to earn profits compared to the speed of operating asset turnover as a measure of business efficiency.
Retained Earning to Total Aset = Retained Earning/Total Aset Earning Before Interent and Tax (EBIT) to Total Asset.
Is an indicator that can be used in detecting problems with the company's ability. Earning Before Interent and Tax (EBIT) to Total Asset = Operating Profit/Total Asset

Market Value Equity
Is a calculation that measures the company's ability to provide collateral for each debt through its own capital which includes the amount of equity and total debt Market Value Equity = Total Equity/Amount of Debt

Sales To Total Liabilities
Is a calculation to measure management's ability to use assets to generate sales. Sales To Total Liabilities = Sales/Total Asset After all calculations are obtained then entered into the formula (Hanafi, 2010: 656), namely:

Z= 1.2 (X1)+ 1.4 (X2)+ 3.3 (X3) + 0.6 (X4) + 1.0 (X5)
To find out which company has a high or low risk level can be seen from the Z-Score, if: 1. A Z-score of less than or equal to 1.81 means that the company is experiencing financial difficulties and has a high risk. 2. Z-Score value between 1.81 to 2.99 means the company is considered to be in the gray area (Gray Area). In this condition, the company is experiencing financial problems that must be dealt with with proper management. If it's too late to handle the company, it can go bankrupt. 3. Z-Score value greater than 2.99 means that the company is in good health so it has a low level of risk.

Definition of Company Size (Size Firm)
The size of the company can be seen from the total assets owned by the company [12]. The size of the company is the number and type of production capacity and capabilities of the company or the number and type of services that can be provided by the company simultaneously to its customers [12]. Company size can be measured by the formula:

Net Profit Margin (NPM)
Net Profit Margin or net profit margin is also called the revenue to sales ratio. The method of measuring this ratio is to compare net income after tax with net sales [13]. Here is the NPM formula: NPM = (Net Profit After Tax) / (Net Sales) Current Ratio (CR) Current ratio is a ratio to measure the company's ability to pay short-term obligations or debts that are due when they are collected as a whole. In other words, how many current assets are available to cover short-term liabilities that are due soon. The current ratio can also be said as a form of measuring the level of safety (margin of safety) of a company. The calculation of the current ratio is done by comparing total current assets with total current debt [14].
Here is the CR formula: Current Ratio (CR) = Current Asset / Current Liabilities Debt to Assets Ratio (DAR) Debt to Assets Ratio is a comparison between total debt to total assets. Total debt includes short term debt and long term debt. Total assets include current assets plus fixed assets and other assets. Debt to asset ratio shows the amount of debt to total assets at a certain time [15]. Every month or every year the position of this ratio can change for better or for worse. Here is the Debt to Assets Ratio formula: Debt to Assets Ratio: Total debt/ Total Assets

II. METHODS
This study aims to examine the effect of net profit margin, current ratio, and debt to asset ratio on financial distress in Poperti and Real Estate sub-sector companies in Southeast Asia for the 2014-2019 period. The type of data used in this research is quantitative data and is secondary data, obtained from chemical sector companies listed on the Southeast Asian Stock Exchange (BEI, SGX, HOSE / HSX, and MYX). This research will use quantitative methods. The quantitative method is called the traditional method, because this method has been used for a long time so that it has become a traditional method for research.

Population and Sample
The population used in this study is the financial statements of the Poperti and Real Estate sub-sector companies in Southeast Asia as many as 35 companies. The samples used in this study were 35 companies with complete financial reports from the 2014 -2019 research year.  From the one sample KS normality test, histogram graph and SPSS P-Plot it can be concluded that the regression model does not meet the normality assumption, it can be seen that the results of one sample Kolgomorov Smirnov statistical test with an asymp sig value. (2-talled) of 0.000, and the normality test with the histogram and P-plot graphs above shows that the normality test is not fulfilled, it can be seen from the graph that does not form a bell and does not follow the diagonal line and then on the P-Plot graph the points appear not follow and move away from the diagonal lines. Because the data is not normally distributed, data outliers or data deletions are carried out, with the initial N totaling 210 to 110 then a second stage normality test is carried out as follows:

Source: Results of data processing for SPPS V21
The heteroscedasticity test image shows that the data has spread below and above zero and does not form a pattern.  Source: Results of data processing for SPPS V21 From the two tables in model 1 above, the results of the effect of Firm Size (Z) on financial distress (Y) on the first output (significant) are obtained because of the sig. 0.002 <0.05 and the interaction effect of Z * X1 (firm size * NPM) on the second output is not significant because of the sig. 0.765> 0.05, it can be stated that in model 1 the Firm Size (Z) is not the Moderator variable.

Autocorrelation Test
Results of the hypothesis model 2 Hypothesis: Firm Size moderates the effect of Current Ratio (CR) on Financial Distress.  From the two tables in model 2 above, the results of the effect of Firm Size (Z) on financial distress (Y) on the first output (significant) are obtained because of the sig. 0.000 <0.05 and the interaction effect of Z * X2 (firm size * CR) on the second output is not significant because of the sig. 0.343> 0.05, it can be stated that in model 2 the Firm Size (Z) is not the Moderator variable.

Results of the hypothesis model 3
Hypothesis: Firm Size moderates the impact of Debt to Asset Ratio (DAR) on Financial Distress