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Proceeding Paper

Success Factors for Using E-Court in Indonesian Courts †

1
Faculty of Law, Primagraha University, Griya Gemilang Sakti Complex, Trip Jamaksari St. No. 1A, Serang 42111, Indonesia
2
Baldwin Boyle Group, GridAKL Building, Wynyard Quarter, 12 Madden St., Auckland 1010, New Zealand
3
Communication Department, Islamic University of Indonesia, Kaliurang St. Km 14.5, Sleman 55584, Indonesia
*
Authors to whom correspondence should be addressed.
Presented at the International Academic Symposium of Social Science 2022, Kota Bharu, Malaysia, 3 July 2022.
Proceedings 2022, 82(1), 58; https://doi.org/10.3390/proceedings2022082058
Published: 16 September 2022
(This article belongs to the Proceedings of International Academic Symposium of Social Science 2022)

Abstract

:
The goal of this research was to investigate whether or not electronic court petitions are beneficial in Indonesia. The proposed research model for analyzing the success criteria for using the case management system was tested in the courts of Greater Jakarta. The model’s explanatory relevance was revealed by using structural equation modeling to examine survey data from 30 attorneys who utilize the system. Furthermore, the significant contribution of system and information quality characteristics is demonstrated. The investigation’s findings have far-reaching implications for both theory and practice. System quality, information quality, and system utilization all have a positive influence on user performance. However, the influence of information quality on usage was not statistically significant. This study adds to the body of research on court management by seeking to implement the success model in Indonesian courts. Furthermore, the study focuses on which parts of the court administration procedure have the most explanatory power. It is recommended that additional research be conducted on the role that technology plays in determining judicial system performance, with a special emphasis on determining the relations between ICT and judicial system performance.

1. Introduction

Electronic government (e-government) initiatives have grown considerably in the past two decades. These projects help governments deliver information and communication technology (ICT)-based information and services. It gives residents, businesses, and the government additional chances to provide better services [1]. ICTs in public administration also help modernize governance and have huge administrative possibilities [2]. This could improve government relationships with communities, businesses, and workers through decentralization, openness, and internal/external responsibility [3,4]. Many sorts of e-government programs are utilized globally in healthcare, education, and transportation. When the judicial system (JS) uses ICTs to improve its efficacy and efficiency, it can ease communication among JS parties (ministry, courts, and prisons) and help improve access to justice and the efficiency of legal proceedings [5]. E-court itself is a set of hardware, software, and networking solutions for the JS to aid court personnel and judges enhance case filing, hearing scheduling, and efficiency. Daily responsibilities include workflow, filing, and hearing scheduling. This research project refers to courtroom and client-courtroom technology as e-court. E-court refers to courtroom technology used globally. According to research on court management, there are two types of court technologies: those used in the courtroom and those used to improve court, party, and public communication [6,7]. This category covers automated registers, case management systems, and financial management systems. First, we have court administration software that helps administrative staff and/or judges (such as jurisprudence databases and sentencing support systems). Second, we have apps that let parties share data and communicate (such as e-filing and provision through court websites). A legal system case registry is automated and helps improve court cases and data access [8].
ICT helps implement the JS’s administrative theory and improve judicial efficiency [9]. Despite significant investments, technical progress is questionable [10,11]. Multiple studies find it to be inconsistent in terms of value for money [12,13]. Previously, court management specialists decided to explore the relationship between technology and individual and organizational performance, mostly using descriptive research [14,15]. This method covers judicial technology, processes, and systems. Unfortunately, no quantitative research has been done on technology and court performance, notwithstanding the court management literature. Moreover, no research has studied how court technology affects lawyers’ IT use (IS). Thus, this study examines how court administrative personnel use e-court applications. With the Indonesian JS’s efforts to digitize all records, judges may be resistant to court technology [16]. This also threatens Indonesia’s justice system. Several countries have used DeLone and McLean’s implementation strategy to analyze IS effects [17], which was also used in this study. Despite academics’ attention to information security, no research has tested this technology in courts. Understanding the efficacy of electronic court applications and the factors that determine their performance is crucial for addressing research gaps and resolving future challenges.

2. Literature Review

The ability to effectively manage or use information systems is the cornerstone of determining the value and utility of information system management and investments. Many academics recognize the need for analyzing the success (or efficacy) of information systems [18]. End-user satisfaction is the most widely used metric for measuring IT performance [19]. Information quality refers to the measurement of the information system’s output, system quality refers to the measurement of the system itself, information use refers to the recipients’ consumption of the output, user satisfaction refers to the recipients’ responses to using the output, and organ quality refers to the overall quality of the organ [20]. System quality, information quality, and information use are all terms that refer to the quality of the system, the information provided by the information system, and how efficiently the information is used. The consistency of the user interface comes first, followed by the quality of the documentation, and last by the system’s failures. Some academics have assessed the quality of systems based on how simple the system is perceived to be or how easy it is to use [19]. When analyzing the quality of information produced by a system, it is vital to take into account the system’s precision, timeliness, and relevance [21]. User satisfaction is described as an individual’s reactions to a set of criteria used to assess a system’s effectiveness [17]. The word user satisfaction refers to a broader sense of contentment with a system’s use than simply using an information system. The usage of information systems can affect user satisfaction at the individual, organizational, and user levels [21]. A successful variable indicates that an information system enhanced a user’s understanding of the decision context, increased the user’s decision-making productivity, influenced the user’s behavior, or influenced the decision maker’s evaluation of the information system’s significance or utility [15]. An effective information system assists users in better understanding the context in which decisions are made.
There are several approaches for quantifying the impact of information on a business. Higher income, increased profitability, and increased return on investment are common measures of organizational effectiveness [15]. The strategy is divided into three stages [17]. The ability of an item to positively influence individuals is referred to as effectiveness. The term technical relates to the accuracy and effectiveness with which information is generated inside the communication system. The ability of information to convey the intended meaning is referred to as its semantic value. The quality dimension assesses the system’s success in terms of its technical aspects, the information quality dimension assesses the system’s success in terms of its semantic aspects, and the effectiveness dimension assesses the system’s success in terms of its efficacy in multiple areas, including utilization, user satisfaction, and individual and organizational benefits. In summary, this is an evaluation of efficacy, quality, and information gathering quality.
The technical levels are determined by the information’s quality, usefulness, and efficiency. The success variables are interconnected rather than independent in this model since it is based on process and cause considerations [16]. This is due to the fact that the model is built on considerations. The model’s creators state that it studies the knowledge of system operations and the effects of those processes, as well as the system’s growth, implementation, and the consequences of those actions. The information system success model has served as the foundation for both academic and empirical research on the efficacy of information and communication technology [20]. DeLone and McLean revised the initial IS success model in response to the findings of studies that called for revisions. Individual and organizational impact have been replaced with net benefits to take into account benefits at any level of analysis, and the quality of service offered is the new criterion for determining whether or not an information system is successful. The information systems success model can be used in the process of evaluating cutting-edge internet-based apps [22].
DeLone and McLean’s success model for information systems has been evaluated in a range of contexts, including commercial, public, voluntary, and mandatory settings [23]. Despite its broad use in assessing the usefulness of ICTs in other public administration (PA) sectors, few studies have looked at the effectiveness of e-government apps using this technique [24]. There have not been many studies looking at e-government from a business perspective. All of these studies begin with the assumption that the success of e-government is more dependent on public participation than on technological improvement. Because user behavior is so important to the success of e-government systems, understanding the elements that influence it is an intriguing issue [25]. The majority of court management research has focused on evaluations of local justice systems, e-justice methodologies, court software development, and user experiences with court technology [26], while user acceptance of intergovernmental services is also critical to the success of an e-government operation [27]. This applies to all e-government rollouts when user participation is critical to e-government success [28].

3. Research Model and Hypotheses

The success of information technology in the judicial system is investigated from the point of view of court administration professionals in this study. These professionals are responsible for utilizing apps in order to carry out their duties when evaluating the technical success, semantic success, and effectiveness of CMS applications, and the effectiveness of CMS applications in general [18], in which key variables apply, such as system quality, information quality, information system use, user satisfaction, and individual impact. These are all considered to be key variables in the assessment. Both the quality of the system and the content are major predictors of user satisfaction and the use of information systems, which are two factors that have an effect on an individual’s level of performance [18]. The majority of research focused on information systems holds the belief that the quality of the system and the output have an effect on user behavior [29], while CMS systems incorporate automated court dockets and other court register processes into the JS. This makes it possible for different court activities, procedures, and practices to be consolidated into a single platform. Employees that have a positive perception of the ease of use, dependability, and timeliness of CMS applications are more likely to utilize it. The combination of previous studies results the construct of this study, as shown in Figure 1.
According to research conducted on information systems, the quality of both the system and the information is an important factor in determining the level of user satisfaction. When clients have the perception that a system is reliable, precise, and punctual, it leads to an increase in user enjoyment and delight, as demonstrated by the following: CMSs are used to automate the activities of administrators and judges within the JS. This gives them the ability to quickly access data and information important to particular cases that have been submitted from any location, at any time, and with no restrictions whatsoever. These systems, as a result of their deployment, have also resulted in the complete description of organizational processes, which includes reading the procedure codes and other applicable legislation, and have also resulted in an improvement in the standardized application of regulations by each court office [17]. It has also resulted in the deployment of these systems, which has resulted in the complete description of organizational processes. As a consequence of this, court employers who place a high value on the quality of e-court applications and output will feel more satisfied with the systems that are now being considered.
As seen in the following explanation, utilization and user happiness are intricately related [20]. In the sense of a process, usage must come before user happiness; however, in the sense of a causal relationship, having a pleasant usage experience will lead to increased user pleasure [20]. In the end, a person’s degree of satisfaction with a system is determined not by how satisfied they are with the system itself, but by how satisfied they are with the results or impacts of their use of the system [23]. Additionally, the impact of use components to system performance has been researched in a range of contexts, such as voluntary and forced settings. For instance, while its contribution may be negligible in a context where participation is a choice, it may be utterly unimportant in a system where participation is mandated. When system utilization is necessary, it is possible that removing use as a success variable is erroneous [21]. This is due to the fact that system use can fluctuate greatly; hence, the variable use must be kept. As a consequence of this, and in agreement with the findings of a number of scholars [21], use is then defined as the degree to which the information system has been integrated into the daily activities of each individual [29]. The contentment level of those who work in court administration rises in proportion to the amount of time spent using e-court applications.
A previous study examined the links between semantic features such information system usage and user happiness, and effectiveness-related variables like an individual’s impact [20]. An empirical study showed that using information systems benefits the individual. Infrequent usage of a system has little effect on an individual’s performance, but consistent use does. Another study found a correlation between user satisfaction and performance in various conditions [21]. User satisfaction is the idea that task requirements and information system capabilities match. There may be a link between user satisfaction and individual influence. Judges and courtroom staff can obtain timely information via a CMS. This improves individual and court performance by shortening the case resolution time. The individual’s performance is likely to be favorably related to their best estimate of the CMS software’s requirements and capabilities.

4. Methodology

The quantitative study was carried out on Indonesian court users, i.e., lawyers, in the Greater Jakarta area. It covered all Jakarta cities and regencies, including Bogor Regency and City, Depok, South Tangerang, Tangerang Regency and City, and Bekasi Regency and City. Questionnaires were collected from 30 attorneys who are able to carry out their duties with the support of e-court content management systems, which are more popularly known as e-court. During a legal procedure, this application is a content management system (CMS) that was developed to help automate court operations and provide assistance. It provides support for case management tasks such as case planning and tracking, and the scheduling of hearings and other court appearances in general. In particular, CMS assists in the operation of the court through the utilization of capabilities that include calendaring and scheduling, docketing, case information management, ticklers, notes, and case linkages.
The comprehensive questionnaire was sent out in February 2022 in order to collect information. In addition to gathering information on user profiles and the e-court software that is being utilized, the questionnaire was designed to investigate the elements that are related with the success of e-courts. In the beginning, comments from both court users and information systems specialists were solicited. This was to undertake preliminary and pilot testing to analyze and validate the approved procedures. Using data from the IS made publicly available in the past, the questionnaire was first crafted, and after that, it underwent testing and analysis. The components had some minor alterations so that they would function better within the e-court program. The purpose of the 15 questions in the survey was to investigate five primary components of the system. These were the quality of the system, the quality of the information, the usage of the system, the happiness of the users, and the individual impact. The ease of use of a system was used as one of the criteria for measuring system quality in the research. The scale consisted of two items. The quality of the information that is produced by e-court applications can be evaluated along three dimensions: the material’s substance, its correctness, and how it is presented.
To evaluate a user’s level of dependence on the information system that was available to them, a reliance measure was applied. The utilization of IS was evaluated based on a single item of this metric. User satisfaction is a measurement of how satisfied users are with a system, and it was computed by modifying a single item based on the work done by Rai and colleagues to capture the level of enjoyment provided by the system [27]. Individual impact, on the other hand, is defined as the extent to which application software was successful in improving the quality of the user’s work, making the end user’s job easier, reducing the amount of time spent on the end user’s job, and assisting the end user in meeting the end user’s job needs and requirements. The four-item user-performance metric was modified in order to arrive at the result. On a scale from one to five, the allegations were rated, with a score of one indicating major disagreement and a score of five indicating strong agreement.

5. Analysis and Results

Based on the Table 1 below, the hypothesis is accepted, i.e., there is an effect of the e-court system quality variable on e-court use. While Table 2 concludes that the hypothesis is not accepted, i.e., there is no effect of the e-court information quality variable on the e-court use. The Sig value is 0.003 < 0.05, as shown in Table 3, the hypothesis is accepted, i.e., there is an influence of the e-court system quality variable on e-court user satisfaction. Moreover, Table 4 shows that the hypothesis is accepted, i.e., there is an effect of the e-court information quality variable on e-court user satisfaction. Table 5 later concludes that the hypothesis is accepted, i.e., there is an influence of the e-court use variable on the e-court use satisfaction. Based on the Sig value of 0.002 < 0.05 in Table 6, it can be concluded that the hypothesis is accepted, i.e., there is an influence of the e-court use variable on user performance.
Lastly, Table 7 shows that the hypothesis is accepted, i.e., there is an influence of the e-court user satisfaction variable on user performance.

6. Discussion

According to this study, the model captures the multimodal and interrelated nature of CMS performance [18], making it a potential court prediction model. The majority of the hypothesized links in the e-court success model were proven, except for the quality-consumption connection. The data show that system quality affects its effectiveness. Previous studies evaluated system quality based on usability [21]. This study found that the time spent using a system increases with its quality and convenience of use. Due to these findings, e-court applications require a high-quality system. Many court clerks lack computer skills and IT experience. Despite CMS being required in courts, administrative officers employ e-court applications since they are easy to use. The content management system (CMS) interface provides straightforward and visible access to content, eliminating the need for organization-wide training and making the system more simply understood and utilized. IT competence strengthens this idea. By using CMS, more court administration officers will be available to complete tasks.
According to the study, the impact of information quality on consumption is not statistically significant. Consider these examples to evaluate CMS content: real-time data access gives consumers fast, accurate information from a database, less erroneous data input, and more consistent data entry over time. Real-time data access also allows users to provide data consistently throughout time. CMS is more significant for judges than court personnel since its output helps judges settle cases more quickly and effectively and plan and organize their operations. CMS output is largely used by courts. Since judges are not required to use CMS, many prefer paper-based paperwork to best utilize employees. Research shows that system quality, information quality, and system use all affect user performance. These findings are compatible with a model [21] for determining an information system’s success. The quality of the information affects user happiness more than the system and how it is used, both of which are important. CMS users in the justice system believe the output is reliable, accurate, and timely. The output of an electronic court application allows administrative employees to swiftly and simply investigate court-docket books and court registers from any location and at any time. Many courts still use paper-based documentation. This study found that the total time spent using a system increases with its quality and convenience.

7. Research Limitations and Conclusions

The primary goal of this study was to investigate the elements that contributed to the effective adoption of CMS as a first step toward a better understanding of the utility of e-courts in Indonesian courts. Because this research is exploratory in nature, there are a number of limitations that must be addressed and taken into account in any future research endeavors. To begin, variable measurement scales are frequently self-report measures, which means they can be skewed, skewing, distorting, and exaggerating the causal relationship between independent and dependent variables. Second, because variable measuring scales are dependent on self-report assessments, they may contain biases. Furthermore, because the study is primarily concerned with analyzing the e-court success model in Greater Jakarta courts, which use a specific type of technology (CMS) and are located in a specific metropolitan area, it is critical to proceed with extreme caution when attempting to generalize the findings to other locations. Additional study, including an assessment of alternative technologies, is required to evaluate the suggested model across a nationwide sample of court users that is representative of the population as a whole and in a range of e-court scenarios, including ones in which participation is voluntary. Finally, one of the research model’s flaws is that it fails to account for the impact of CMS on the daily operations of the judicial system as a whole.
In order to better comprehend the utility of e-court technologies from the perspective of court administration staff, the study focuses on the effects of CMS on individual user performance. Furthermore, because the research model was only employed in two unique courts and no attempt was made to conduct a longitudinal analysis, it cannot assess court efficiency in terms of organizational structure. The first step, however, in acquiring a better understanding of the overall effectiveness of the court system is to conduct an evaluation of the performance of court administration staff. The study’s goal was to obtain a better understanding of information technology’s success in courts and to add to a long-running debate among e-justice authorities, scholars, and practitioners. According to the study’s findings, the ease of use and output of the deployed systems are important factors in determining the efficacy of CMS adoption in courts. This finding has far-reaching implications for court administration theory and practice. It adds to the body of studies on court management by aiming to implement the success model in Indonesian courts more frequently. Furthermore, the study focuses on which parts of the court administration procedure have the most explanatory power. It is recommended that additional research be conducted on the role that technology plays in determining judicial system performance, with a particular emphasis on determining the relationship between information and communications technology (ICT) and judicial system performance.

Author Contributions

Conceptualization, A.L.; methodology, A.L.; software, I.D.; validation, I.D.; formal analysis, I.D.; investigation, M.R.; resources, M.R.; data curation, M.R.; writing—original draft preparation, A.L. and I.D.; writing—review and editing, A.L. and I.D.; visualization, I.D.; supervision, A.L.; project administration, A.L.; funding acquisition, Not Applicable. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bernroider, E.W.N.; Koch, S.; Stix, V. A comprehensive framework approach using content, context, process views to combine methods from operations research for IT assessments. Inf. Syst. Manag. 2013, 30, 75–88. [Google Scholar] [CrossRef]
  2. Yildiz, M. E-government research: Reviewing the literature, limitations, and ways forward. Gov. Inf. Q. 2017, 24, 646–665. [Google Scholar] [CrossRef]
  3. Currie, W.; Guah, M.W. IT-enabled healthcare delivery: The U.K. National Health Service. Inf. Syst. Manag. 2006, 23, 7–22. [Google Scholar] [CrossRef]
  4. Lussak, A.; Abdurachman, E.; So, I.G.; Setiowati, R. The effect of operational improvement on business survival with moderating role of continuous improvement (Case study: Food and beverage small business in Bali). Int. J. Sci. Tech. Res. 2019, 8, 617–621. [Google Scholar]
  5. Commission of the European Communities. Towards a European E-Justice Strategy; The European Parliament and the European Economic and Social Committee: Brussels, Belgium, 2018. [Google Scholar]
  6. Reiling, D. Technology in courts in Europe: Opinions, practices and innovations. Int. J. Court Adm. 2012, 4, 1–10. [Google Scholar] [CrossRef]
  7. Velicogna, M. Use of Information and Communication Technologies (ICT) in European Judicial Systems; Commission for the Efficiency of Justice: Brussels, Belgium, 2018. [Google Scholar]
  8. Kiškis, M.; Petrauskas, R. ICT adoption in the judiciary: Classifying of judicial information. Int. Rev. Law, Comput. Technol. 2004, 18, 37–45. [Google Scholar] [CrossRef]
  9. Fabri, M.; Langbroek, P.M. The Challenge of Change for Judicial Systems. Developing a Public Administration Perspective; IOS Press: Amsterdam, The Netherlands, 2020. [Google Scholar]
  10. Hamin, Z.; Othman, M.B.; Mohamad, A.M. Benefits and achievements of ICT adoption by the high courts of Malaysia. IEEE Symp. Humanit. Sci. Eng. Res. 2012, 2, 1233–1238. [Google Scholar] [CrossRef]
  11. Palumbo, G.; Giupponi, G.; Nunziata, L.; Mora-Sanguinetti, J. Judicial Performance and Its Determinants: A Cross-Country Perspective; OECD: Paris, France, 2018. [Google Scholar]
  12. Commission for the Efficiency of Justice (CEPEJ). European Judicial Systems. Efficiency and Quality of Justice; Commission for the Efficiency of Justice: Brussels, Belgium, 2020. [Google Scholar]
  13. World Bank. Doing Business; World Bank: Washington, DC, USA, 2018. [Google Scholar]
  14. Azmi, Z.T. Using technology to improve court performance: Malaysia’s experience. Asia Pac. Judic. Reform Forum Conf. 2020, 37, 195–220. [Google Scholar]
  15. Contini, F.; Cordella, A. Information system and information infrastructure deployment: The challenge of the Indonesian e-justice approach. Electron. J. E-Gov. 2017, 5, 43–52. [Google Scholar]
  16. DeLone, W.H.; McLean, E.R. Information systems success: The quest for the dependent variable. Inf. Syst. Res. 1992, 3, 60–95. [Google Scholar] [CrossRef]
  17. Wang, Y.S.; Liao, Y.W. Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Gov. Inf. Q. 2008, 25, 717–733. [Google Scholar] [CrossRef]
  18. Petter, S.; DeLone, W.H.; McLean, E.R. Measuring information systems success: Models, dimensions, measures, and interrelationships. Eur. J. Inf. Syst. 2008, 17, 236–263. [Google Scholar] [CrossRef]
  19. Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 2019, 13, 319–340. [Google Scholar] [CrossRef] [Green Version]
  20. Lussak, A. Triple A Strategy to Improve Supply Chain Performance in Semarang City SMEs. Int. J. Sci. Technol. Res. 2020, 9, 218–222. [Google Scholar]
  21. Petter, S.; McLean, E.R. A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Inf. Manag. 2009, 46, 159–166. [Google Scholar] [CrossRef]
  22. Lussak, A.; Abdurachman, E.; So, I.G.; Setiowati, R. The effect of financial performance, service and product innovation on the survival of small businesses mediated by TAM. Int. J. Innov. Creat. Change 2019, 7, 259–275. [Google Scholar]
  23. Prybutok, V.; Zhang, X.; Ryan, S. Evaluating leadership, IT quality, and net benefits in an e-government environment. Inf. Manag. 2008, 45, 143–152. [Google Scholar] [CrossRef]
  24. Teo, T.S.H.; Srivastava, S.C.; Jiang, L. Trust and electronic government success: An empirical study. J. Manag. Inf. Syst. 2008, 25, 99–131. [Google Scholar] [CrossRef]
  25. Casanovas, P.; Sartor, G.; Casellas, N.; Rubino, R. Computable Models of the Law; Springer: Berlin, Germany, 2018. [Google Scholar]
  26. Cerrillo, M.; Fabra, P. E-Justice: ICT in the Court System; IGI Global: Hershey, PA, USA, 2018. [Google Scholar]
  27. Contini, F.; Lanzara, G.F. ICT and Innovation in the Ublic Secor; Pelgrave: London, UK, 2018. [Google Scholar]
  28. Hung, S.Y.; Tang, K.Z.; Chang, C.M.; Ke, C.D. User acceptance of intergovernmental services: An example of electronic document management system. Gov. Inf. Q. 2009, 26, 387–397. [Google Scholar] [CrossRef]
  29. Doll, W.J.; Torkzadeh, G. The measurement of end-user computing satisfaction. MIS Q. 1988, 12, 259–274. [Google Scholar] [CrossRef]
Figure 1. Research framework.
Figure 1. Research framework.
Proceedings 82 00058 g001
Table 1. E-court system quality and e-court use.
Table 1. E-court system quality and e-court use.
ModelSum of Sq.dfMean Sq.FSig.
1Regr.5.10615.1066.2810.018 b
Residual22.76128813
Total27.86729
Dependent Variable: EU. b. Predictors: (Constant), ESQ.
Table 2. E-court information quality and e-court ese.
Table 2. E-court information quality and e-court ese.
ModelSum of Sq.dfMean Sq.FSig.
1Regr.3.08513.0853.4860.072 b
Residual24.78228885
Total27.86729
Dependent Variable: EU. b. Predictors: (Constant), EIQ.
Table 3. E-court system quality and e-court user satisfaction.
Table 3. E-court system quality and e-court user satisfaction.
ModelSum of Sq.dfMean Sq.FSig.
1Regr.4.25514.25510.6260.003 b
Residual11.21228400
Total15.46729
Dependent Variable: EUS. b. Predictors: (Constant), ESQ.
Table 4. E-court information quality and e-court user satisfaction.
Table 4. E-court information quality and e-court user satisfaction.
ModelSum of Sq.dfMean Sq.FSig.
1Regr.3.45213.4528.0460.008 b
Residual12.01428429
Total15.46729
Dependent Variable: EUS. b. Predictors: (Constant), EIQ.
Table 5. E-court use and e-court user satisfaction.
Table 5. E-court use and e-court user satisfaction.
ModelSum of Sq.dfMean Sq.FSig.
1Regr.2.86412.8646.3630.018 b
Residual12.60328450
Total15.46729
Dependent Variable: EUS. b. Predictors: (Constant), EU.
Table 6. E-court use and user performance.
Table 6. E-court use and user performance.
ModelSum of Sq.dfMean Sq.FSig.
1Regr.54.023154.02311.2320.002 b
Residual134.677284.810
Total188.70029
Dependent Variable: UP. b. Predictors: (Constant), EU.
Table 7. E-court user satisfaction and user performance.
Table 7. E-court user satisfaction and user performance.
ModelSum of SquaresdfMean SquareFSig.
1Regr.157.7821157.782142.8900.000 b
Residual30.918281.104
Total188.70029
Dependent Variable: UP. b. Predictors: (Constant), EUS.
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MDPI and ACS Style

Romdoni, M.; Lussak, A.; Darmawan, I. Success Factors for Using E-Court in Indonesian Courts. Proceedings 2022, 82, 58. https://doi.org/10.3390/proceedings2022082058

AMA Style

Romdoni M, Lussak A, Darmawan I. Success Factors for Using E-Court in Indonesian Courts. Proceedings. 2022; 82(1):58. https://doi.org/10.3390/proceedings2022082058

Chicago/Turabian Style

Romdoni, Muhamad, Assed Lussak, and Ibnu Darmawan. 2022. "Success Factors for Using E-Court in Indonesian Courts" Proceedings 82, no. 1: 58. https://doi.org/10.3390/proceedings2022082058

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