Keywords

Training, NGO-Business, Government, Profitability, Welfare

JEL

R23; R28.

Introduction

Small to Medium Enterprises (SMEs) are essential for economics around the world, especially in developing countries. The statement of World Bank that SMEs account is that up to 60% of the total available work, which accounted for up to 40% of the national income (GDP) in developing countries. This statistic will be highly significant if it takes into account formal and informal SMEs. Besides, Ndeye (2018) said, that the World Bank also estimated 600 million employments has been entrained in the global work for the next 15 years, especially in Africa and Asia, the role of SMEs continues toward the development process. SMEs are recognized as sectors that play an important role in economic development (OECD, 2012). Governments at various levels have conducted initiatives to promote the growth of SMEs (Patrick, 2009). SMEs have been seen to contribute to the economy directly through the provision of new products and services, job creation, and economic growth. Thus, the healthy and sustainable economic growth of SMEs has been needed for activities in the economy so that SMEs have a living standard that increases overall and the development of social Welfare (OECD, 2011). Even in general, the development of SMEs can accelerate the achievement of economic objectives and broader economic development, including increasing the profitability of entrepreneurs (Saani, 2012). SMEs have been instrumental in developing economic activities and economic growth in developing countries.

Moreover, in the few last decades, activities management of the business and accounting researchers has demonstrated a consistent effort in researching in the small- medium enterprises (SMEs). According to Affirmed (2018), small-medium enterprises play an important role in economic development between developed and developing countries. Globally, SMEs represents 99% of businessmen activities in the world. However, Small-Medium enterprises have become one of the interesting subjects for business activities and accounting management. Mesnner (2016) said SMEs also faced problems relating to business sustainability as a result such as globalization, technological advancement, intensive marketing competitiveness which can be changed in management business and constraint of capital funding. Senftlechnner & Hieble (2015) say, to activities in businesses for survival and remaining sustainable, they needed to take into account financing information and nonfinancial information. The impact of globalization is increasingly complex, demanding the business world to cooperate and create different innovations in shaping the world's work network. Dhian (2015) says, one of the different ways manifested in globalization is in the minimization the role of the Government, especially in economic development, and replacing it with a market mechanism. The Era of globalization has evolved the free trade paradigm in which the government's role in every aspect of economic development is minimized, and replaced by free-market forces that have spread across the country and around the world.

In developing countries such as Indonesia, SMEs are also a very important part of national economic development. According to Jaswadi (2015), in all aspects of business in Indonesia, 99% in the small-medium enterprises' units, with these sectors employed more nearly 97% of all existing workforce. SMEs have accounted for 16% of total activities business and accounted more for 57% of the total of Indonesia's current Gross Domestic Product (GDP). (Centralized statistics bureaucracy, 2016). Small-medium enterprises can be playing an important role in economics and contributed to quantitative and qualitative indicators. Small-medium enterprises in Indonesia have contributed to developing entrepreneurship, creativity and innovation, worker and employment, economic growth, and economic development. SMEs have acted as an indicator of overall economic growth. The important thing to note is that SMEs in Indonesia always contributed more than 50% to the overall GDP. So, the fact is shown if they have substantially contributed to national economic development.

This shows that entrepreneurs engaged in SMEs contribute to the economic growth in Indonesia. Small and Medium Enterprises (SMEs) can contribute significantly to the national economy. Central bureaucracy statistics (2016) explains, post-economic crisis 1997-1998 the number of SMEs was not reduced. The case is still increasing and is even able to absorb 85 million of the 107 million jobs there, up to 2012. SMEs are as much as 56,534,592 units or 99 percent, and the remaining one percent or 4968 unit sectors are large enterprises. In 2015, the number of SMEs was expected to reach 60.7 million units and the most were micro-scale enterprises by 98%. SMEs growth in the period 2011-2015 reached 2.4 percent with the largest growth was a medium-sized business in the amount of 8.7 percent. The growth of small and medium enterprises is higher than that of micro business growth in the past five years can indicate increased business class, as well as investment returns on a medium scale, recorded an average of 15.7 percent. In the same period, the capacity of SMEs to absorb labour continues to increase by 5.9 percent. In 2015, the SMEs workforce reached more than 132.3 million workers.

So in general, the contribution of SMEs in economic activities strongly support the increase of gross domestic product (GDP), but the SMEs in Indonesia does not acquire good and adequate empowerment, so it does not develop to the fullest. Therefore, the entrepreneurs of SMEs cannot demonstrate the maximum and optimal business performance. Based on this fact, the Government needs to implement empowerment of SMEs, namely by providing business training, an incubator in business and regulation that supports SMEs business, and the help the capitalization to develop SME businesses.

Literature Review

SME Empowerment

Definition and meaning of small-medium enterprises are very large among many countries in the world. Generally, there is disagreement on the differentiation of micro for smaller companies. Small businesses of medium and medium enterprises are large corporations. However, in general, medium enterprises usually employ less than five employees who work if full-time. In Indonesia, Small Business is a company with five to nineteen workers and in other countries more than that. Medium enterprises have a job of about 20 to 50 employees. According to Tambunan (2008), the definition and meaning of being used for statistical purposes may be variations of them to use for corporate policies or programs. All countries have definitions of SMEs to be statistically purposed. Many countries also have a definition of policies purposed. This definition is often different for meaning used in statistically purposed, as it is also different for industry with the policies programming. SMEs can bring part-time business without hiring workers or non-business enterprises that are often called self-employment. In fact, the traditional business which made shell handicrafts in the Java countryside in Indonesia has smaller semiconductor producers who employed 10 people or more. Most companies that make up this category of SMEs are small with 70% to 80% from the employed not less than 5 people. There is only a small fraction of the company; usually the range is about 1% to 4%, which has more than 100 employees. Unfortunately, there is no consistent definition for medium enterprises in the country.

Several definitions in Indonesia of SMEs, they have depended on which bureaucracy gives definition. Ministry of Cooperative State and SMEs using Small Business Law number 20 of 2008, which defines Small Enterprises as a business unit with total initial assets up to IDR 300 million (about the US $22,000 at the current exchange rate), excluding land and buildings, or with a maximum sales annually valuing of IDR 1 billion (the US $70,000), and medium Enterprises must a business unity in annual sales value of more than IDR 1 billion but less than IDR 50 billion.

Although the law does not explicitly define Medium Include Enterprises and the SMEs assess the data on Small Enterprises including Medium Intra Enterprises. The Cantered of Bureaucracy Statistic (BPS, 2016), where regulated conducting SMEs surveys, using several workers as the basis for determining the size of the company. In definition, Medium Intra Enterprises, Small Enterprises, and Medium Enterprises are business units with respectively, 1-4, and 5-19, and then 20-99 workers, and Large Enterprises is a unit with 100 or more workers. The Department of Industry defines companies with the size of the number of workers as the SMEs definition. Human resource management is precisely directed, can contribute to increasing competitiveness, and deny profit on the market share of each sector. Employee empowerment is one of the main concepts of human resource management. The specificity of human resource management in SMEs is the result of autonomy work, development of workers less than maximum, in small companies than is happening in large corporations.

Empowering employment means encouraging them to become professional and engaged in decisions or activities that affect their work. That means giving them a chance to showed that they increased their skill and up with a good idea and they have the knowledge and skills to develop these ideas into implementation. According to the OECD (2012), empowerment, both in terms of individuals and organizations, is a multidimensional enhancement. From this organization, it has defined seven-dimensional empowering, such as: powering, decision-making, well informative, autonomies policy, initiative and creativities, knowledge and skills, responsibilities. Researchers, and some of them, only emphasized the transfers of power from above to the lower level of the organization and focus on this dimension alone (OECD, 2016). The empowerment process is researched linkage with: Character manager, organizational characteristics and information technology that the outcome of its empowering with considered to be referring for duty and worker satisfaction, have loyalties behavioral and the worker commitment. The relationship between empowerment and performance of the company or employee innovation has been well researched. (Anna, 2017).

Government's Role to Support SMEs

The government's role in making policies of countries around the world has to recognize the essential participant about small-medium enterprises in local and international economies. Muhammad (2017) said policies of studying from OECD, OIC, EUC, and APEC sought to a formulation for effectiveness, efficiencies about policies measurements and optimally for encouraging the improvement of SMEs roles. The fact of keyword determinant shell is considered for the SMEs assistance program to be effective. Firstly, governance is very important to identify the whole problem of SMEs toward business activity. Governments can consider the business problem to be different about SMEs faced. The difference of prejudice is unusual, so become for not effective business capital relief programs. Secondly, the government must have, several cantered or focus that leading for all the assistance of business capital given by various agencies/ministries at various levels. Thirdly, should be beneficiary gain of capital assistance program is support a momentary act to overcome currently of business barriers, must be developed up the ability of SMEs to address some of the problems of business in the within their controlling around (European Commission, 2007). Fourth, it is also important that governments can identify with potential businesses to be developed in the future to participate in the SME Empowerment program (OECD, 2008).

According to Kusumawardhani (2015), although the Government's desire to encourage SME's activities in the global market, so eliminate the business problem, its business capital aid can’t be effective based on accurate the identifying of businesses problem faced by SMEs. Governments may have their perception of a business problem, and then they are can be different in SMEs (OECD, 2008). As a result, Governments and SMES may be different in understanding the types of problems that business, or different in understanding the severities, so the urgency of addressed any problem. This misunderstanding can lead to an imperfect input for the policy-making process, which in turn will lead to ineffective business assistance programs. These misunderstandings may come from inadequate governmental resources and or mechanisms for collecting news, so collecting input for less complete SMEs. (Jerome, 2005).

SME Profitability

Increased profitability has become one of the important objectives of business activities. To improve the welfare of business actors, law and regulations will be effectively established and protected proprietary rights, business actors, and enforcement of financial transactions related to the business advantage. The converse in regulations and taxes will be a negative impact on the company's performances. Klapper, et al., (2006) found that an interesting regulation of tax too large would impede the creation of new ventures. Research conclusion, in this case, is bad business environmentally maybe about affected SMEs performances due to restrictions and competition of imperfections and growth of the slow company. The impact of proprietary institutions and institutions that guarantee profits from the company will increase growth and high profitability. Proprietary and business benefits will be more important for business expansion and improvement of its business activities. Meanwhile, the rule of law is preferred for the guarantee of property rights and business benefits as well as a wider increase in business. It is because business advantage is the most dominant parameter to improve the welfare of SMEs so that business actors always strive to increase their business profitability.

Community Welfare

Community welfare is a complex functional system and is related to value, purpose, intention, a general government program. The dimensions of welfare form a system of objective and subjective relationships between the peoples included in life activities. Anikina (2015) says, the recommended models of prosperity are studies and estimated, that sources of activities and economic development to in various sectors. Community welfare is an effort designed with an international approach that exists in the features of national characteristics. Increasing economic activity can mean setting up a better future. Subroto (2017) says, the cost to be paid to prepare a more prosperous future is to increase business activity in various aspects of Mother Care. According to Marques (2016), the distribution of the production proceeds should be used to set the cost of economic activities and call defensive costing. Ivankina (2015) says prosperity implies proof of self-confidence of about personality or community has in the reality of situations because it meaning to gain for welfare to be possible to external factors and internal factors. In the fact, social welfare is a complicated problem for an integral indicator of the efficiency of the social sphere that reflects social health, welfare standards, quality of life, and social security of the Community system. Social welfare is giving from civil societies and interest in achieving and regulated must be a balance between individual and communal. Ivankina (2013) says, about civil societies representatives of moralities and policy of organization from the community in the communities their demonstration of phenomena in society dynamics, if peoples utilities they are in the meaning to survivals, liberties for choice and activity is primarily for use of valuing. According to Subroto (2015), prosperity is kindly of chronotype from sociality developing that becomes a character from normal regulation changes. Meanwhile, the welfare of sociality is a cultural policy aimed at the stabilizing of the axiological system and the norm that allows everyone to save feeling and peace.

Conceptual of Thinking

Based on the purpose of research, data analysis will be performed using Structural Equation Modeling (SEM) which is a collection of techniques statistically and that allow the testing of relative complex serial of relationships and simultaneous.(Figure 1)

Description of the models:

(X1) = Training to Business; (X11= Materials to Training); (X12 = Incubator).

(X2) = NGO of Business; (X21 = Solidarity); (X22 = Networking); (X23 = Motivation)

(X3) = Role of Government; (X31 = Regulation); (X32 = Capital Aid); (X33 = Supporting).

(Y1) = Profitability (Y11 = Output of Business); (Y12 = Profitability from Business);

(Y13= Asset for Business); (Y14) = Opportunity to Business).

(Y2) = Welfare Society (Y21 = Income of Business);(Y22= Riches from Business); (Y23 = Satisfaction).

Method of Research

A survey approach is used here as the research methodology to describe the role of empowerment businessman in implementing its SMEs to foster profitability for welfare society in Indonesia. A survey can be used for exploratory and descriptive research and is useful in providing answers for how and why questions. Respondents of this research are 340 businessmen from implementing in SMEs with selected by cluster 10 businessman every province in Indonesia. The data analyzed here were collected from various sources, such as questionnaires, a document from the Centered of Statistic Bureaucracy, and included are academic literature. (Bahl & Milne, 2006). Data were analyzed with the use of Structural Equation Modeling (SEM). Structural equation modeling was also known is used to assess the relationship between the construct recently, it is a widely used statistical tool in social science research (Anderson, 2012). Recently, it is a widely used statistical tool in social science research. The usage of SEM has increased even more since the 1990s (Hershberger, 2003).

Result of Research

Test Result Normality of Research Instrument Data

Test data normality is done to observe the critical value that is considered to be abnormal spread, test results assessment of normality of AMOS 4.0 program. If the value of C. r > +2.58 then categorized data distribution is abnormal, therefore cases that do not meet the assumption are not included in subsequent analysis. The normality test count results can be seen in the following Table 1:

Table 1 Result of Normality Assessment of Normalities
Var	Min	max	scew	c.r.	curtosis	c.r.
X11	20	25	-0.282	-1.57	-0.896	-2.495
X12	23	36	-0.28	-1.56	-0.531	-1.479
X21	9	15	0.201	1.12	-0.18	-0.5
X22	12	18	0.126	0.702	-0.615	-1.713
X23	9	15	0.16	0.892	-1.046	-2.912
X31	8	13	-0.252	-1.404	-0.947	-2.637
X32	10	15	-0.278	-1.545	-0.974	-2.71
X33	5	14	-0.557	-3.1	-0.367	-1.023
Y11	3	15	0.19	1.058	-0.625	-1.741
Y12	16	36	-0.007	-0.037	-0.622	-1.732
Y13	10	30	-0.426	-2.373	0.005	0.015
Y14	9	14	0.22	1.224	-1.185	-3.298
Y21	10	15	0.24	1.216	-1.174	-3.318
Y22	8	15	0.106	0.591	-0.946	-2.633
Y23	7	14	0.23	1.232	-1.179	-3.328

From the results of the above calculations on this study, all data qualified testing assessment normality CR doesn’t exist which exceeds 2.58. So it can be categorized as normal data distribution.

Outliers test Result Research Instrument Data

Evaluation of the Outliers is done by observing data that has a Z score of more than 3. Results from the Z score test can be seen in Table 2. If from the observation there is a case that has Z Score > 3, it will not be included in the subsequent analysis, but if the sample is more than 80 respondents then the range of Z Score between 3 to 4 means in this study the number of samples 186 respondents then that is said to happen outliers when Indigo Z Score> 4 (Ferdinand: 2000). Based on Table 1 above there is no indicator of the variable that the Z score value is > 4, so from the 20 variable indicators there is nothing outlier.

Table 2 Result of the Z Score Test Descriptive Statistics
Indicators	N	Minimum	Maximum	Std. Dev
Zscore: Training	340	-2.2071969	2.1992999	1
Zscore: Incubator	340	-3.0351933	1.3007971	1
Zscore: Solidarity	340	-1.7138505	1.7297194	1
Zscore: Networking	340	-1.6190505	1.7537555	1
Zscore: Motivation	340	-1.3908703	1.6407923	1
Zscore: Regulation	340	-1.7816477	1.3925522	1
Zscore: Capital Aid	340	-1.9400031	1.4919046	1
Zscore: Supporting	340	-1.4734879	1.7445405	1
Zscore: Business turnover	340	-1.8223682	1.4685103	1
Zscore: Profitability	340	-2.2552299	1.8916491	1
Zscore: Output of Business	340	-1.6494133	2.1459377	1
Zscore: Project of Business	340	-1.9275687	1.906953	1
Zscore: Income of Business	340	-2.6916184	2.1199243	1
Zscore: Satisfaction	340	-1.8783537	1.7992651	1
Zscore: Asset to Business	340	-1.8907283	2.2272513	1
Zscore: Welfare Society	340	-2.6973182	2.3467595	1

Conceptual Model Test Results

The test conceptual model is intended to know whether the conceptual model that has been developed by researchers based on theoretical studies, as well as past research, exists in alignment with empirical reality. If the analysis test results in a model that has not been aligned, the model simulation step will be done by first observing the modification indices and correlated errors. Thus the model simulation is intended to produce an empirical model that has the best degree of alignment. Test the initial model according to the conceptual model of the research, which results can be seen in Figure 2 as follow.

Based on the initial model, the structural equation is obtained as follows:

Based on the test results the initial model was not entirely obtained the qualified coefficient. Detailed model alignment results can be seen in the following Table 3:

Table 3 The Structural Equation of the Original Model Appropriate Conceptual Model
No	Structural Equations
1	Profitability =0,44 Training + 0,20 NGO + 1,64 Government
2	Welfare = 2,65 Profitability + 0,97 Training + 0,79 NGO + 1,40 Government

Based on Table 4 above, it seems that many test requirements alignment models can not be fulfilled. Thus the test result of the preliminary model corresponds to the conceptual model empirically has not fulfilled the requirements of model alignment.

Table 4 Original Model Alignment Test Results Based on Conceptual Model
Alignment Model	Criteria	Coefficient Result	Coefficient
Chi Square	Small	213,870	Too big
Significant Probability	>0,05	0,000	Not met
CMIN/DF	< 2,00	2,577	Not met
GFI	>0,90	0,879	Not met
AGFI	>0,90	0,824	Not met
TLI	>0,95	0,654	Not met
CFI	>0,95	0,727	Not met
RMSEA	<0,08	0,92	Not met

The initial model obtained has not fulfilled the requirements of model alignment, so the researcher performs a simulation of modification of the model by observing the modification Index (modification indices), either based on basic model (basic model) as well as from correlated errors. Has not fulfilled the requirements of the alignment model because it still appears to load the below-required factor of < 0.4, so the need for modifications by eliminating some indicators of the variables. Indicators that do not qualify on this initial model and need to be eliminated are as follows: Education quality variables (Y2) include; Semester Exam (Y22). The results of the original modified model appear in the first phase of the simulation test, as shown in Figure 2.

Test Model Alignment Simulation

In the simulation test, the following models will be presented, two models. The following will be shown in succession to two models that have been identified. The two models will then be compared to be determined one model that has the best alignment.

Structural Model Results of the First Stage Simulation

The first model to be successfully identified with structural equation model analysis looks like in Figure 3 as follow

Based on the first alternative model, the structural equation obtained is as follows.

Based on the first stage model test results, the Chi-Square coefficient has not been obtained (which requires small or non-significant numbers), GFI, AGFI, TLI, and CFI (not yet meet the more than 90 equivalent) as well as the P-Value coefficient which is still far below 0.05 (the significance of the requirements required. Detailed model alignment test results can be seen in Table 5.

Table 5 Structural Equations of First-Stage Models
No	Structural Equations
1	Profitability=0,41 Training+0,19 NGO +1,70 Government
2	Welfare=2,58 Profitability+0,19 Training+0,79 NGO+1,55 Government

Based on Table 6 it can be declared a structural model of the first stage simulation model has not been met the requirement to be said as a unified model, has not fulfilled the requirements alignment model due to the value of P-value, GFI, AGFI, TLI, CFI, and RMSEA has not fulfilled the required. This information is then used as the basis for creating the next stage simulation, as shown in Figure 4.

Table 6 First Stage Model Alignment Test Results
Alignment Model	Criteria	Coefficient Result	Coefficient
Chi Square	Small	147,544	Fulfilled
Significant Probability	>0,05	0,000	Not met
CMIN/DF	< 2,00	2,108	Not met
GFI	>0,90	0,902	Fulfilled
AGFI	>0,90	0,852	Not met
TLI	>0,95	0,761	Not met
CFI	>0,95	0,810	Not met
RMSEA	<0,08	0,0774	Not met

Structural Models Result In Second Stage Simulation

The second phase of the simulation is to reduce the structural model as shown in the following figure 4:

Based on the alternate model of the second stage, the structural equation obtained is as follows.

Based on the third stage model test results it turns out to be qualified model alignment. Detailed model alignment fulfillment can be seen in the following Table 7.

Table 7 Structural Equation of Second Stage Model
No	Structural Equations
1	Profitability =2,25 Training + 1,29 NGO + 0,86 Government
2	Welfare = 4,02 Profitability + 2,58 Training + 0,82 NGO + 0,97 Government

Related to Table 8, it can be expressed structural model of the second phase simulation model does not find any miscorrelation between covariant. This can be said that the model obtained has fulfilled the element of alignment of the model and converge and produce a significant influence between variables.

Table 8 Second Stage Model Alignment Test Results
Alignment Model	Criteria	Coefficient Result	Coefficient
Chi Square	Small	71,585	Fulfilled
Significant Probability	>0,05	0,241	Fulfilled
CMIN/DF	< 2,00	1,119	Fulfilled
GFI	>0,90	0,950	Fulfilled
AGFI	>0,90	0,918	Fulfilled
TLI	>0,95	0,974	Fulfilled
CFI	>0,95	0,982		Fulfilled
RMSEA	<0,08	0,025		Fulfilled

Comparison of Structural Model Analysis Results

After displaying the structural model obtained from the analysis results ranging from the original conceptual model, the first stage model simulation to the second stage, it is necessary to set one structural model that has the best goodness of fit index. Results of these studies, with indicator used as the basis for determining from modeling to fulfill from the coefficient of P-values, and GFI, and then AGFI, and TLI, then CFI so to fulfill for chi- squared (X2 with the smaller degree to freedom (df). In Table 9, the following is a comparison of the model alignment coefficient of the five selected models.

Table 9 Comparison of Model Alignment Test Results
Alignment Model	Criteria	Early Models	Model Stage I	Model Stage II
Chi Square	Small	213,870Too big	147,544Fulfilled	71,585Fulfilled
Significant Probability	>0,05	0,000Not met	0,000Not met	0,241Fulfilled
CMIN/DF	< 2,00	2,577Not met	2,108Not met	1,119Fulfilled
GFI	>0,90	0,879Not met	0,902Fulfilled	0,950Fulfilled
AGFI	>0,90	0,824Not met	0,852Not met	0,918Fulfilled
TLI	>0,95	0,654Not met	0,761Not met	0,974Fulfilled
CFI	>0,95	0,727Not met	0,810Not met	0,982Fulfilled
RMSEA	<0,08	0,92Not met	0,0774Not met	0,025Fulfilled

Result of testing and displaying the structural model obtained from the analysis results comparisons from the original conceptual model, the second stage model simulation to the Table 10 bellow.

Table 10 Model Structural Equations Results Comparison
Model	No	Structural Equations
Early Model	1 2	Profitability=0,44 Training+0,20 NGO+1,64 Government Welfare=2,65 Profitability+0,97 Training+0,79 NGO+1,40 Government
Model Stage I	1 2	Profitability=0,41 Training+0,19 NGO+1,70 Government Welfare=2,58 Profitability +0,19 Training+0,79 NGO+1,55 Government
Model Stage II	1 2	Profitability = 2,25 Training + 1,29 NGO + 0,86 Government Welfare =4,02Profitability + 2,58 Training + 0,82 NGO+ 0,97Government

Noting Table 10, apparently found models that have a good model alignment, namely the second model. The second Model is best reviewed from the acquisition of the largest P-Value coefficient, the smallest CMIN/Df, the largest GFI, the largest AGFI, the largest TLI, the largest CFI, and the smallest RMSEA. The determination of the second model as the best model is based on the adequate coefficient of alignment of the model as well as the resultant pattern of relationship between significant variables. After successfully finding the new findings model as seen in the second stage simulation test, the next step is to test the measurement model/Confirmatory analysis factor used to know how many relations between variables and indicators. The confirmatory test factor is performed by comparing the loading coefficient factor (α) and significantly at a rate of α=5%, as shown in the following presentation.

Test Result (Measurement Model/Confirmatory Analysis Factor)

After the test of the assumption above and found a model that has a good alignment, then conducted data analysis to get a clear picture of each of the variables. The results of the analyses done for each of the variables in the study can be described as follow Table 11: ←

Table 11 The Influence Of Training Ngo And Government On Profit And Welfare
No	Variable	Co- efficient Line	S.E	C.R Terms>1,96	Probability < 0,05	Description
1	Profitability←Training	2.25	0.258	2.716	0.006	Significant
2	Profitability←Incubator	1.29	0.08	2.523	0.012	Significant
3	Profitability←NGO	0.66	0.505	1.96	0.05	Significant
4	Welfare←Incubator	0.82	0.405	1.96	0.05	Significant
5	Welfare←Training	2.58	0.58	2.831	0.005	Significant
6	Welfare←NGO	0.97	1.341	1.043	0.297	Not
7	Welfare←Profitability	4.02	1.346	1.967	0.049	Significant

According to Table 11 above, the CR value and the probability of its significance at the level of significance (α)=0.05, can be found that the training and business assistance as follows:

1. Business training for SMEs positively affects the profits of the business, meaning hypotheses are accepted.

2. Business mentoring positively affect the increase in business profits, which means hypotheses accepted

3. Non-governmental organizations in SMEs have a positive effect on the increase in business profits, so hypotheses are acceptable.

4. Business assistance positively influences the welfare of SMEs.

5. The training of business activities aid by the Government, positive influence on the welfare of SMEs.

6. Organization of non-governmental organizations in the field of SMEs has not a positive effect on the welfare of SMEs.

7. The increase in business profitability has a significant effect on increased SMEs' welfare.

Discussion

Training and Mentoring Business for SMEs

This section will be discussed in the findings of the results which have been described in the previous sections. The result of the discussion in this analysis is bases on empirical findings as well as previous theories and researches relevant to the research conducting. The result of this discussion is intense to explain the suitability also about inter-connectedness from the dependent variable and independent variable.

From tests used the AMOS 4 program utilizing Structural Equation Modeling analysis, results of testing against between models through overall and measured tests be ably described that multistage models can explain the phenomenon of businessman welfare in some important aspects (Marcellinus, 2016). Testing results in this study give a clear result about the multilevel model is very good in explaining the training models and incubator against SMEs to improve the welfare of SMEs actors can prove the hypothesis.

By analyzing the influence of empowerment on SMEs that include exercise business, Non-Government Organization (NGO) about SMEs and the role of government in the regulation and capital assistance to the benefits and welfare of SMEs is expected to be able to understand that the empowerment of government and NGO will affect the increase of profits that in the end can affect the welfare of SMEs in Indonesia. The result of testing and analysis found a model their connected about at five parameters purpose of the concept modeling. These5 variables include Training, NGO, government roles, benefits of business, and SMEs welfare.

The parameters about the five identified variables, the researcher usually eliminated one variable because of the in-eligible loading factor, the indicator of welfare variables that is satisfaction in implementing SMEs. So that the indicator is still able to use as a variable gauge is as follows:

1. Training variables are measured through indicators: materials and training activities in conducting business, and incubator implemented against SMEs businesses. Of these two variables are the most responsible for mentoring in conducting business.

2. Variable role of NGO in SMEs activities. Variables in indicators include solidarity, networking, and mutual motivation. About three variables are jointly able to clarify the variables and from the three variables that are most capable of explaining the variables are solidarity between fellow SMEs, cooperation in capturing business opportunities then mutually motivation to conduct business SMEs

3. The role variable of the government is measured by the indicators: the assistance of business capital, a regulation that encourages SMEs, and the exhibition of SMEs business products. These three parameters are joint be able to clarify the variables within the three parameters that are most capable of explaining variables are variables are the assistance of business capital, followed by regulations that encourage SMEs, and the exhibition of products of SMEs enterprises. In line with opinions stating that business capital is important in increasing the benefits of SMEs business.

4. Variable gains are measured through indicators: income generation seeks the profit in conducting business, Assets used for business capital, intelligence in capturing business opportunities. These four parameters are collectively able to confirm he variables with I the four parameters that are most capable of explaining the variables are the assets or capital for the effort then followed by the profits in the business, then the intelligence in capturing business opportunities and the last is the asset to the business. It is in line with the findings of Gill (2012) where is stating that assets are important factors to carry out the business activities of SMEs.

5. The welfare variables for the SMEs perpetrators are measured through indicators: income gained from the business, then the wealth owned, and the last satisfaction and confidence in carrying out the business. These three parameters are joint be able to clarify about welfare variables of SMEs. Of these three variables are be able to clarify of the variables of the business income or profits gained in conducting SMEs, then the magnitude of wealth that has the result of business and satisfaction in developing its SMEs business.

The study in line with Subroto (2015) who found a new model such as the above, also found the influence between the training variables that are training materials, business practices, and business assistance to the magnitude of profit and improvement of the welfare of SMEs as the result of hypotheses test. It is in line with the findings of Kraus (2019) that presents the importance of training and mentoring efforts to increase the benefits of SMEs business in Indonesia.

Role of Non-Governmental Organizations in SMEs

In the results of the descriptive analysis found by SMEs in Indonesia, it is generally a sufficient benefit. The high advantage is supported by training and business mentoring, the Solidarity and cooperation between SMEs, and the role of the government in assisting business capital as well as supporting regulation, as its attributes. The means by analysis of Structural Equation Modeling, it is has found that the benefits of SMEs were influenced by the training and mentoring of the businesses he received. The above test results were found there the three parameters and can be used as a gauge in clarifying the advantage variables are: training, NGO and business mentoring. These three parameters are joint be able to clarify the variable of profit acquired by SMEs. Of the three indicators that are most capable of explaining is business training then business mentoring and the ultimate is the role of government in encouraging SMEs business.

The results of this analysis can be conclusion result from the testing with the analyses of Structural Equation Modeling means by AMOS 4.0 program showed about SMEs empowerment jointly positively affect the profits of the proceeds. This finding shows of the results are linear with there is expression. Suyanto (2010) says, stating that: The strategy of empowerment to increase MSME profit is a commitment to the larger SMEs in increasing profitability and has gained much attention from various researches on current SMEs empowerment. Increased profitability and training as well as mentoring efforts are seen as a key strategy that can increase the benefits of SMEs. Therefore, the relationship between empowerment, training, and profit impact can be developed to increase the profits of SMEs players in Indonesia.

By integrating the training and business mentoring in SMEs in Indonesia can develop a model for the empowerment of SMEs actors in increasing the profit of the business, which can eventually increase prosperity. According to Marta (2018), if stating that profits from the business can be beneficial for a change in one's motivation and behavior. The relationship between empowerment and business advantage is correlated. Also in line with Subroto (2017) it states that the business training factor is essentially the base capital for the business, which covers aspects of training materials and business mentoring and business practices by SMEs. The improvement of skills during the training, mentoring, and encouragement by the Government, is the attribute of increased business profits. Spithoven (2013) says that SMEs empowerment has increased the business profit that supports prosperity. The findings support the research results of Owusu (2018) in their study; especially the empowerment has three indicators, namely: training and mentoring, NGO and the role of Government have supported the increase in SMEs profit. About three parameters are joint be able to clarify the empowerment variables, from the three parameters that are more capable of explaining is the training of business, followed by business mentoring, then the last one is the aid of effort risk by the government. It is in line with stating that to increase business profit with the empowerment program against SMEs; the Government should prioritize the training and mentoring business and the assistance of business capital for SMEs in Indonesia.

Role of Government toward SMEs to Aid Loan Capital and Regulation

Results of a description from analysis founding in the improvement of business profits and wealth of SMEs in Indonesia became the benchmark of SMEs welfare. The analysis of SEM indicators that can explain the welfare variables is the size of the results of the business, the wealth owned by the business actors, and the satisfaction in carrying out the business. These three parameters are joint be able to clarify the interaction between variables in this research. Of the three parameters that are more able to clarify is the magnitude of the results of business and wealth obtained from the business of SMEs then satisfaction and confidence in doing business. While the empowerment of SMEs is measured through indicators: training, business mentoring, and roles. These three indicators are jointly able to explain the SMEs empowerment variables and from the three parameters are more capable of explaining the variables are training then incubator followed by the assistance of capital from the government, and the latest solidarity between SMEs in Indonesia.

The results of the above SEM analysis can be the conclusion of testing results with the analysis of SEM mean by the program AMOS 4.0 showed that not all indicators of empowerment affect the welfare of SMEs in Indonesia. Only two of the empowerment indicators that affect the improvement of welfare are training and mentoring business for SMEs. Meanwhile, the role of NGOs does not affect SMEs' welfare improvement. This indicates these results are not linear with as stated by Spithoven (2013) that SMEs empowerment has an influence on the increase in the benefits of SMEs which include: the size of business results, assets for the business, and creativity in reading business opportunities. There is no way of finding this because the data obtained cannot describe the role of NGO in the cooperation of SMEs to increase the profitability and welfare of SMEs.

The research found that the government's business capital support has been able to increase SMEs' profits significantly. This result is supported by the findings of Lamsah (2018), who say that government policy can act as stimuli in increasing SMEs profits. This research also supported the findings of Tambunan (2018) which found that the lack of government assistance became one of the causes for the declining business advantage of SMEs. The argument related to this finding that: (1) The Government's commitment to improving the welfare of MSME is demonstrated by the Government's seriousness in providing business capital assistance, making regulations that encourage SMEs, (2) Quantitative description of the respondent mentioning some of the respondents have been getting the help of business capital in the form of soft credit and business assistance and included in the exhibition/exhibition in This research findings in line with the findings of the Agung, et al., (2018) where stating that the assistance of business capital in the form of soft credit and business assistance greatly affects the increase in business profits for SMEs. The same result with the research was discovered by Rafiki (2020), who said that the government's help and policy strongly support the increase in the benefits of SMEs businesses. The role of government that is widely accepted by SMEs is in the form of soft credit assistance for business capital and training as well as mentoring business that aims to help SMEs to increase their business profitability.

The discussion above shows the importance of the Government's role in encouraging SMEs to increase business profitability, especially the policy that protects SMEs in conducting business activities in their respective field. This argument is given to the findings of this research which is essentially the role of the government is very influential in the activities of SMEs business in Indonesia to increase business profits and develop its business to compete in regional and international areas.

Limitation of Research

There are several limitations in this study, among others as follows:

1. The relationship between the influence of training variables and the mentoring of business towards increased profits, there is also the possibility of being influenced by other meters.

2. This research is only based on SMEs actors in Indonesia, so the results of this research cannot be used as a generalization basis on international scale business activities.

3. The approach used in this research is quantitative with data collection through poll distribution. Fully realized to explore data about activity and motivation to strive, the quality of data obtained by the poll technique is determined by the honesty of the respondent in providing answers. There may be no respondents in providing answers.

4. Variable measurements of the profit and social welfare of SMEs actors, only based on the profit and income of business and assets owned in support of his business.

Conclusion

Results of the research have been conducted on the role of empowering Small Medium Enterprises to increased welfare society the following conclusions are obtained as Training to business can be foster profitability of businessman. A non-government organization in SMEs has not significant be foster profitability of businessman. Motivation to develop of business has a significant effect to foster profitability. The role of government for businessman has a positive effect to foster profitability. However, the performance of businessmen and the role of government is the dominant factor to foster profitability for increased welfare in businessman society.

Acknowledgement

The authors are grateful to the Head of Economics Education, Faculty of Economics, and State University of Surabaya for funding the research. Also to thank Patmoko for helping analyzing data and for all anonymous students who collected data for this study?

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