Procurement of Goods/services itself is one of the largest sources of corruption in public financial sector. Jasin et al (2007) explained that around 70 percent corruption cases handled by the Corruption Eradication Commission when this is the practice of corruption in the procurement of goods and services for government. Widely, Tuanakotta (2014) explains the factors that open opportunities for fraud, when the individual officials have absolute sovereignty/(monopoly power), the corresponding officials have concession authority (discretion), individual/officials need not accountable (accountable) against their actions, and they operate in an environment that is not transparent (low of transparency). While specifically in the procurement of goods/services for government un

Contractually obligated to relationship between the principal and the agent can also cause the behavior of opportunistic infections. When one of the parties has mastery of specific information, this will cause the existence of asymmetrical information (Halim and Abdullah, 2016). Principal/agents tend to exploit the situation for the exchange of information for pushed the significance of each (Singh and Sindersmukh, 2000). In the short term contract relationship, information asymmetry between principal and agents tend to higher, preferably in the relationship long-term contracts, information asymmetry is likely to be smaller (Amagoh, 2009). Mastery of this information also shows the lack of transparency between the principal and the agent.

Information and Communication Technology (ICT) offers a new approach for private organizations, the government, or other institutions to create transparency and encourage the anti-corruption (Bertot, et al:2010). According to Azmi et al. (2015), e-procurement can be 'gatekeeper' for all participants in the tender to ensure that they follow the rules that have been set in the system, using e-procurement all bidders must fulfill all the requirements when the condition is not met then automatically bidders will fall. In addition, e-procurement system does not bias, this system choose the best value (best value) of all the contract, this system also can restrict or stop the political and economic pressure that tries to intervene in the procurement process, there is no compromise in this system, each tender participants are required and required to provide evidence of their ability (e.g., evidence, experience qualification certificate). This system is transparent and no partiality, with less human interaction.

Public Universities, as one of the government institutions in the field of education, would also carry out the procurement of goods/services through e-procurement. The implementation of e-procurement on the level of State Universities also based on the Presidential Regulation Number 54 year 2010 regarding the procurement of goods/services for Government. Each year to support education in Indonesia, the government gives a portion of the budget in the State Budget (APBN) or local budget for the education sector. Of the total government budget, around 20 percent had to provide for this sector, on 2016 the government budgeted funds approximately Rp416 Trillion for the education sector and Rp39,66 Trillion allocated for state universities (http://www.dikti.go.id/informasi-publik/laporan-keuangan/, accessed on April 27 2017). With the college manages the vast amount of the budget, then misappropriated budget such as corruption, bribes, and others must be limited. But the question is whether the intention to adopt e-procurement system on the STATE UNIVERSITY influenced by the desire to limit the risk of corruption? According to Ajzen (1985), intention is assumed as something that underlies the behavior. The adoption of e-procurement is a way to alter the conventional procurement process to modernize the public procurement process to automate and integrate every part of the procurement process to improve efficiency, transparency, and accountability in the public sector, improve the performance of the government and reduce the digital divide (Neupane, et al:2012).

Based on the background of the problem then arranged the formulation of the research problem: 1) Whether the strength of monopoly influence the intention to adopt e-procurement system on the State Universities in Surabaya?; 2) Whether the asymmetric information influence the intention to adopt e-procurement system on the State Universities in Surabaya? 3) Whether transparency and accountability influence the intention to adopt e-procurement system on the State Universities in Surabaya?

This research aims to test the influence of the strength of monopoly, asymmetric information and transparency and accountability to the intention to adopt e-procurement on State Universities in Surabaya

The dependent variables in this research are the intention to adopt e-procurement. The variable will be measured using several questions that will be answered by respondents with Likert scale indicator, with 4 points (1= Strongly disagree, and 4 = Strongly agree).

The dependent variables of this research are the strength of the asymmetric information monopoly, transparency, and accountability. Each variable is measured using several questions that will be answered by respondents with Likert scale indicator, with 4 points (1= Strongly disagree, and 4 = Strongly agree). Independent variables measured with the indicator developed from the research 2014 Neupane, et al.

1. Monopoly power is defined as a condition or situation when public officials have absolute authority to impose regulation and policy (Mistry and Jalal, 2012).

2. The asymmetry of information Rahmah et al. (2014) is a condition where one of the parties has more information than the other party. Independent variables the asymmetric information will be measured with the indicator developed from the research Neupane, et al (2014) .

3.Transparency (information disclosure), namely openness in implementing the decision-making process and openness in the proposed judicial review and relevant information regarding the company Kaihatu (2006). While accountability is the clarity of the function of the structure of the system and the accountability of the organs of the company so that the management of the company implemented effectively.

The type of data that is used in this research is the primary data because it is a research data obtained directly from the source. The data collected from the results of the questionnaire charging by respondents related to the influence of the strength of monopoly, Asymmetric Information and transparency and accountability to the intention to adopt E-procurement on State Universities in Surabaya that collect using questionnaires.

Research respondents is involved in the process of good e-procurement e-Tendering will or e-purchasing namely power budget users (KPA), officials PPK), and procurement services unit (ULP) at state universities in Surabaya. In this research, all state university prepared to become respondents. The spread of the questioner done in January until February 2017, with a total questioner that spread as much as 70 copies.

The questionnaire back as much as 33 questionnaire from seven State university or 47,14% from the total population of research, so that the total of the questionnaire that was used for the data processing by 33 questionnaire from seven State university.

This research using Structural Equation Model (SEM) with Partial analysis model This Square (PLS) to test the hypothesis that used. Analysis of PLS is tested with the help of software WarpPLS 5.0 for windows to examine the relationship between the influence of the strength of the asymmetric information monopoly, transparency and accountability and intention to adopt e-procurement.

Five indicators, namely: KM1-km5 formed monopoly power variable. The asymmetric information variables created by five indicators, namely: He1-HE5. The variables transparency and accountability were formed by eight indicators, namely: TA1-TA8. The variables of intention to adopt e-procurement created by the six indicators, namely: The NME NME16.

The measurement of the outer model performed with reflective measurement indicator is judged based on the correlation between the score item or component the score being estimated by the value of the outer loading factor. The minimum value of the outer loading factor from a proper indicator is used to reflect a variable is a 0.5. The initial structural model used in this research can be seen in picture 2 below.

Based on the results of that found in figure 3 and table 2, all the indicators that make up the change has the value of the outer loading factor greater than 0.5. These can be deduced that all the indicators are worthy of being made the indicator that can represent each of the variables in accordance.

The measurement of the discriminant validity is to compare the value of the square root of Average Variance Extracted (AVE) every change with a correlation between the change in the model. The value of the AVE recommended must be greater than 0.30 or have the value of the p-value smaller than equal significance (0.05). The measurement result discriminant validity in this research can be seen in Table 3 below.

Based on the results of that are located on table 3, all the variables have discriminant validity value higher than 0.5 and p-value smaller than equal significance (0.05). This can be deduced that all valid variable and can be trusted. After the variables are valid, then the test is done the reliability of all the variables used in this research. They are testing the reliability of the variables using the technique of composite reliability. To view the reliable or whether or not a measure is done through the coefficient reliability and when the reliability coefficient greater than 0.70. The measurement results in composite reliability in this research can be seen in table 3 above. Based on the results found in table 3, all the variables have the value of composite reliability greater than 0.70. This can be deduced that all variables reliable and reliable to be used in further analysis.

Testing the inner model done to measure the overall relationship between the variables in this research. The measurement of the inner model is done to know the level of the influence of the relationship between the variables and the level of the influence of the overall relationship of the variables in the system built. The measurement of the inner model to test the relationship between the variables in the research used it said the value R². It told the based R² a model can be classified as strong (≤ 0.70), medium (≤ 0.45), and weak (≤ 0.25). While the relationship between the variables in the system that is built on research is calculated by using the value of the predictive relevance (Q²) aims to assess the predictive validity of independent variables. The predictive validity of independent variables said well when having (Q²) greater than zero. And presented in Table 4.:

Based on table 4. above can be known that it said the value R² from variables intentions to adopt e-procurement of 33.5 percent by monopoly power variable, asymmetric information and transparency, and accountability. This indicates that the model compiled can explain the phenomenon of the influence of the strength of monopoly, asymmetric information, and transparency, and accountability to the intention to adopt e-procurement of 33.5%. While another variable can explain the rest of 66.5 percent is not examined in this research. To view the overall relationship of the variables in the system built in this research and obtained the value of Q² intentions to adopt e-procurement of 0,431 greater than zero, so that meet the criteria of a good predictive validity.

The fit model tests used to measure the model fit is good through the indicators to fit the value of the APC (Average Path greatly enhanced), ARS (Average R²), AARS (Average R-Square), and AVIF (Average Block Variance Inflation Factor). APC (Average Path greatly enhanced) is a measurement of the average path coefficient which is located in a research model, received value for APC seen from P-Value produced namely ≤0.05. ARS (Average R-Square) is a measurement of the average value of R-Square (R²) which is located in a research model, received value for ARS seen from P-Value produced namely ≤0.05. It said the AARS ( Average R-Square) is a measurement of the average it said the value R-Square (R²) which is located in a research model, received value for AARS seen from P-Value produced namely ≤0.05. AVIF (Average Block Variance Inflation Factor) is the size of the fit a research model to evaluate the problem in this colinearity model partial square (PLS). If happened multicolinearity (predictors of predictors in a model of mutual correlates), then the value of the higher AVIF, received value limit for AVIF is ≤3.3 and still be tolerated until on the value of 5. (Ghozali and Latan, 2014)

Though based on the results of the data on Table 5. shows that the model in this research stated fit, Apc, ARS, and AARS have a p-value less than 0.05. While the value of AVIF <3.3 shows that there are no multicollinearity problems between the indicator and the variables used.

The influence of the strength of monopoly against the intention to adopt e-procurement in this research is analyzed using the model of partial this square. Test results in the influence of the strength of monopoly against the intention to adopt e-procurement can be seen in table 6.:

Based on the results in table 6, it can be concluded that the strength of monopoly influence the intention to adopt e-procurement. This can be seen from the P Values of 0,027 under 0.05. Based on the value of the estimation of regression coefficient produced, amounting 0,301, it can be concluded that the strength of monopoly positive effect on the intention to adopt e-procurement. The value of a positive regression coefficient shows the relationship between the direction of the strength of the monopoly and intention to adopt e-procurement, namely if the strength of monopoly increases one time, then the intention to adopt e-procurement will increase of 0,301 times.

Based on the value of the P values and regression coefficient to see the influence of the strength of monopoly against the intention to adopt e-procurement, it can be concluded that the strength of monopoly positive effect to the intention to adopt e-procurement. This shows that hypothesis 1 (a) stating that the strength of monopoly positive effect on the intention to adopt e-procurement proved to be significant.

The influence of the information asymmetry of intentions to adopt e-procurement in this research is analyzed using the model of partial this square. Test results the influence of the information asymmetry of intentions to adopt e-procurement can be seen in the Table 7 below:

Based on the results in table 7, it can be concluded that the information asymmetry influences the intention to adopt e-procurement. This can be seen from the P Values of 0,045 under 0.05. Based on the value of the estimation of regression coefficient produced, amounting 0,269, it can be concluded that the information asymmetry of positive effect on the intention to adopt e-procurement. The value of a positive regression coefficient shows the relationship between the direction of the asymmetry of information and intention to adopt e-procurement, namely if information asymmetry increases one time, then the intention to adopt e-procurement will increase of 0,269 times.

Based on the value of the P values and regression coefficient to see the influence of the information asymmetry of intentions to adopt e-procurement, it can be concluded that the information asymmetry of positive effect on the intention to adopt e-procurement. This shows that hypothesis 2 (two) stating that the asymmetric information positive effect on the intention to adopt e-procurement proved to be significant.

The influence of transparency and accountability to the intention to adopt e-procurement in this research are analyzed using the model of partial this square. Test results influence of transparency and accountability to the intention to adopt e-procurement can be seen in table 8.:

Based on the results in table 8, it can be concluded that the transparency and accountability of influence the intention to adopt e-procurement. This can be seen from the P Values of 0,028 under 0.05. Based on the value of the estimation of regression coefficient produced, amounting 0,300, it can be concluded that the transparency and accountability of a positive effect on the intention to adopt e-procurement. The value of a positive regression coefficient shows the relationship between the direction of transparency and accountability and intention to adopt e-procurement, namely if transparency and accountability increased one time, then the intention to adopt e-procurement will increase of 0,300 times.

Based on the value of the P values and regression coefficient to see the influence of transparency and accountability to the intention to adopt e-procurement, it can be concluded that the transparency and accountability of a positive effect to the intention to adopt e-procurement. This shows that hypothesis 3 (three) transparency and accountability of a positive effect to the intention to adopt e-procurement proved to be significant.

Hypothesis 1 received. In this research, five indicators are used to measure the strength of monopoly namely, (a) e-procurement provides a real-time information, (b) reduces the monopoly or selection of remedy (e.g.: vendor/supplier) that special before in the process of the contract, (c) increase internal efficiency on the whole process of procurement, (d) e-procurement reduce the possibility of fraud or accounting error (error), (e) e-procurement help provide the contract with fixed price. Through the test statistics of the two considered significant indicator is (a) e-procurement provides information that real-time, with a real-time procurement information automatically ease of control over the entire process of procurement accounting and with a real-time procurement information so the public can participate in monitoring the procurement process through the internet anytime and anywhere by offering openness of access to the community and can reduce the monopoly of certain officials (b) reduces the monopoly or selection of remedy (e.g.: vendor/supplier) that special before in the process of the contract, then through the test statistics of the three indicators are not considered significant namely (c) e-procurement increase internal efficiency on the whole process of procurement, (d) e-procurement reduce the possibility of fraud or error Accounting (error), (e) e-procurement help provide the contract with fixed price. Research in the Neupane, et al. (2014a) all monopoly strength indicator has a value of loading factor above 0.5 so that it can be said that all the indicators are significant and valid. A difference in the value of the loading factor in this research can be caused by the variation of the existing data in the less variety indicator or evenly. The result of this research shows that there is a positive relationship between the variables the strength of monopoly to adopt e-procurement (β=0.30, P=0.03).

Hypothesis 2 received. In this research, five indicators are used to measure the information asymmetry namely, (a) e-procurement help increase competition in terms of the quantity (participation) and terms of quality (openness and justice) between all bidders in the tender process (b) provides information up-to-date, (c) help track and monitor all the procurement process, (d) reduce discretion, (e) and consistency in the procurement process. Through the review of the statistics it is known that the four indicators stated valid and significant and of the indicators are not considered significant namely (a) e-procurement help increase competition in terms of the quantity (participation) and terms of quality (openness and justice) between all bidders in the tender process. In research, Neupane (2014) indicators that have the value of the outer loading low is the three indicator (HE3), namely e-procurement helps track and monitor the entire process. A difference in the value of the loading factor in this research can be caused by the variation of the existing data in the less variety indicator.

Lapsed into four indicators that declared valid and significant in reducing the information asymmetry, namely (b) provides information up-to-date. (C) Help track and monitor all the procurement process, automation of the procurement process through e-procurement also facilitate antidote to oversee the procurement process such as track manufacturing process and obtain all information that is associated with the procurement, in e-procurement every antidote to get the same information (d) reduce discretion, according to Boehm and Olaya (2006) more projects, assets or product auctioned is unique and a specific then the higher the risk of corruption, because the scope for higher discretion, besides that corruption can also appear on the complex contracts where clarity on the initial offer will open the way for discretion, but in e-procurement discretion this can be avoided because the information and requirements regarding the proposal is specified clearly in the system and information This is open to all the participants in the tender (e) consistency in the procurement process, rules, and regulations that have been specified apply to all bidders who have registered. All the item helps reduce the asymmetry of information in the public contract. The result in this research shows that there is a positive relationship between the asymmetric information variables to adopt e-procurement (β=0.27, P=0.04).

Hypothesis 3 received. In this research, eight indicators are used to measure the transparency and accountability of namely, (a) technology e-procurement helps the procurement process more transparent and accountable, (b) e-procurement help reduce human error, (c) e-procurement services make more comfortable in obtaining information, (d) All government procurement policy, process and guidelines available online (e-procurement), (e) e-procurement provides better relations between public officials with Remedy, (f) e-procurement brought increased public information transmission time (g) e-procurement increase the availability of public information such as offers and other processes, (h) e-procurement can improve the accuracy of our.

Through the test statistics, four indicators are not considered significant, and four indicators considered significant. Four indicators that are considered not significant namely (b) e-procurement help reduce human error, (c) e-procurement services make more comfortable in obtaining information, (g) e-procurement increase the availability of public information such as offers and another process, (h) e-procurement can improve the accuracy of ours. In research, Neupane (2014) all indicator of transparency and accountability variable has a value of loading factor above 0.5 so that it can be said that the indicator is valid and reflect the latent variable. A difference in the value of the loading factor in this research can be caused by the variation of the existing data in the less variety indicator.

Then the four considered significant indicator is (a) technology e-procurement helps the procurement process more transparent and accountable. (D) all government procurement policy, procedure and guidelines available online at portal e-procurement, not like the procurement system in a paper-based, the electronic system procurement presents various information in the procurement portal (e) e-procurement provides better relations between public officials with remedy for e-procurement system reduces the interaction of face-to-face between public officials with providers, through e-procurement system this interaction decreases because the entire procurement process from both the registration, aanwijzing, evaluation and announcements done electronically through e-procurement system so that can prevent corruption and build the trust of the community and increase transparency and accountability. (F) Deals, e-procurement brought increased public information transmission time. All these factors have an essential role in the government/public officials to increase transparency and accountability and help reduce corruption. The results of this research show that there is a positive relationship between transparency and accountability to adopt e-procurement (β=0.30, P=0.03).

Test results and analysis shows that the strength of monopoly positive effect on the intention to adopt e-procurement and proven to be significant. ) Is supported by the research Neupane et al. (2014a), Neupane, et al. (2014b), Azmi, et al. (2015), Mistry and Jalal (2012), and Ahmad, Al-Mutairi and Thuwaini (2013). This result proved that e-procurement has the potential to limit the risk of corruption by reducing the strength of the monopoly of public officials, so that affect the intention to adopt e-procurement on State Universities in Surabaya.

Test results and analysis shows that the asymmetric information positive effect on the intention to adopt e-procurement and proven to be significant. ) Is supported by the research Neupane et al. (2014a), Neupane, et al. (2014b), and Balsevich, et al. (2011). This result proved that e-procurement has the potential to limit the risk of corruption by reducing the asymmetric information on the process of public procurement of goods and services electronically, so that affect the intention to adopt e-procurement on State Universities in Surabaya.

Test results and analysis shows that the transparency and accountability of a positive effect on the intention to adopt e-procurement and proven to be significant. ) Is supported by the research Neupane et al. (2014a), Neupane, et al. (2014b), Singh (2009), Kim, et al. (2009), and Haque and Pathrannarakul (2013). This result proved that e-procurement has the potential to limit the risk of corruption to increase transparency and accountability in the procurement process of goods and services electronically, so that affect the intention to adopt e-procurement on State Universities in Surabaya.