ON INFORMATICS VISUALIZATION

— Since typical classrooms do not include discussions, collaborative learning, or interactive learning activities, engagement is a major challenge in distant learning. Online learning satisfaction levels should be measured as evaluation material for future implementation. Although online learning has many advantages, a high dropout rate remains a significant challenge. This study investigates how higher education students' engagement and satisfaction with online learning are enhanced by information, system, and service aspects. The research design was quantitative research, and we used a questionnaire to collect data. The questionnaire was designed on a five-rating interval scale. The sampling technique was simple random sampling. The target minimum sample was counted using the Slovin method, and 206 undergraduate students taking online courses were surveyed online. The model was tested using structural equation modeling partial least squares (SEM PLS). This method is useful for investigating the relationship between constructs. The model was tested with the application of the SmartPLS program. The results revealed a positive and significant effect of system quality, information quality, service quality to student engagements, and their impact on student satisfaction, both direct and indirect. This study answers the literature gap and verifies the importance of online learning quality factors on students’ satisfaction and engagement. These results are expected to help to improve online learning in higher education settings, specifically on students' engagement and satisfaction, leading to perseverance and success.


I. INTRODUCTION
Students must establish an active learning environment that encourages more people to pursue online education.This is essential for improved student experiences, academic success, and retention rates [1].In higher education, significant efforts have been made to involve students in collaborative notetaking and boost their engagement with the material for more substantial and expressive learning [2].Distance learning reduces social connection, student well-being, and studentteacher engagement in general.Creating digital content that promotes active learning and student participation makes it challenging.E-learning is made possible by several factors, including the Learning Management System (LMS) (communication gateway), educators (content authors), teaching staff (teacherstudent link), and students (LMS users) [3].The educational sector frequently discusses using technology in lecture sessions to improve teaching and learning activities.
Engagement in all treatments shows that novelty technology affects engagement [4].
Previous research studied the antecedents of behavioral intention to use and actual use based on the Technology Adoption Model (TAM) or Unified Theory of Acceptance and Use of Technology (UTAUT) [5], [6], [15], [16], [7]- [14] and its extensions, but fails to support a vital construct truly reflects online learning, namely customer engagement.Other studies apply the Delone, and McLean IS success model but again fail to support customer engagement [6], [12], [17]- [21].Thus, this study was conducted to answer the literature gap and verify the importance of service quality, information quality, and system quality factors on student satisfaction and their impact on student engagement.
High levels of participation during classes and tutorials positively impact students' performance.Because behavioral and cognitive engagement functions are exciting, evaluation, thinking, and technology advancements influence students' attendance and involvement in class.There are critical debates on whether attendance or behavioral and cognitive engagement affects performance.Attendance is distributed through technology and students' evaluative thinking, which aids in investigating how official attendance and class engagement are connected.Using internet platforms to deliver slides in class impacts students' attentiveness.This implies that attendance at tutorials and courses is not an issue compared to the criteria utilized.
An online learning system offers the flexibility to study without time limits, geographic location, and physical appearance, attracting most students.Online learning can be carried out anywhere and anytime, and students can manage their studies and plan time for work and family.Although online learning has many advantages, a high dropout rate remains a significant challenge.
Lectures use monotonous methods on learners, leading to stress, boredom, and complaints regarding assignments.Therefore, evaluation is necessary for effective online learning.Interaction between students, lecturers, and tutors during online learning is ideal for dealing with isolation and separation feelings.The Learning Management System (LMS), characterized by the management of lesson content, learning processes, evaluations, online exams, subject administration, chat, and discussion, is an integrated and comprehensive system used as an e-learning platform.In general, e-learning content availability varies from institution to institution, depending on the provider (Higher Education).This is due to the lack of a standard to regulate the content to be used.After implementing E-learning, its effectiveness and positive impact on learning is a significant concern.Moreover, student engagement in online education is essential to increase student satisfaction.This research examines how to improve student satisfaction from the system, information, and service quality, mediated by student engagement in distance learning education.

II. MATERIALS AND METHOD
When using an information system, the information is relevant, easy to comprehend, timely, and completes the data received [22].Since the introduction of the current IS success model in 2003, several studies have supported its utility and application, including ePortfolio [23], online learning [24], [25], and the e-learning 2.0 system [26].
Information quality is a critical component of education and may affect the learning system in case it is poor.However, it can be a system's accomplishment, particularly in online classes or mobile learning.System quality involves easily utilizing information systems to affect the intention to use it.The information includes the system's availability, response rate, user-friendliness, and screen features (interface).A poor quality system results in students' dissatisfaction [22].In case it becomes complicated to use, deliberate attempts to destroy it are made.In our study, a learning management system refers to a system used to present and publish information.It includes technical features that affect students' perceptions of the quality of web platforms.
Service quality refers to how a user is assisted and responded to in information systems.This includes genuine attention in resolving a problem, personalization, trust, and understanding of the user's individual needs [22].Service quality takes precedence as the main tool for service quality.The service quality model continues to be a reliable tool for evaluating service quality in various service sectors, including the education sector [27].Study shows that information, system and service qualities, user satisfaction, intention to use, and net benefits help to achieve the intended use of technology in online learning [6], [12], [17]- [21].
Engagement refers to the time and effort students devote to instructional activities.Teaching desires can easily be achieved depending on students' efforts and dedicated time [28].Students' purposeful behaviors or practices effectively show academic growth [29] and boost participation and learning [30].In general, engagement has proved to be essential in determining learning outcomes [31], [32].Academic engagement is the students' effort to perform well in class and achieve their goals [29].This involves a cognitive process, active participation, and emotional involvement in learning methods, assignments, or values.However, previous studies did not emphasize engagement with its aspects, including behavioral, cognitive, and emotional engagement [33].The benefits of classroom involvement on performance are primarily found in elementary and high school education studies [33], [34].Scales for gauging classroom involvement are either designed for study or are challenging to translate to the Indonesian distance learning higher education scene.Furthermore, class size is an essential aspect of Indonesian higher education.For instance, 240 students enroll in economics or business management courses.
Perceived satisfaction is among the critical marketing principles to be implemented in online learning and significantly affects user behavior intentions (Caruana et 2020).Users' may willingly stick to technology depending on their level of satisfaction and perceived utility [3], [35].Satisfaction is the level at which a student expresses pleasant feelings about a service interaction.Furthermore, users' delight depends on confirmation and perceived usefulness.Studies show that collaborative learning information exchange can be supported by an e-learning system [36], [37].Web-based solutions help create, exchange, perceive knowledge, and build a virtual community for collaborative and interactive learning [38].Moreover, interactive communication may be affected by different services in the information system (IS).According to studies, information, system, and service qualities affect student satisfaction [3].
Therefore Student Engagement Based on the literature study, the conceptual model in Fig. 1 was generated based on the literature study to investigate the correlation between system, information, and service qualities, student satisfaction, and engagement.This study used an exploratory design to understand the questions and capture the exploratory findings in the related descriptive studies.The data was collected over a "one shoot" cross-sectional once in a certain period for a particular subject.Specifically, questionnaires with a scale of 1 to 5 (where 1=strongly disagree, and 5 = strongly agree) were used to collect data.The unit of analysis was undergraduate students in Jakarta, Indonesia.A total of 206 respondents were selected using a random probability sampling technique.
The Partial Least Squares-Structural Equation Modeling (PLS-SEM) method was used to analyze the relationship between variables through the SmartPLS version 3 application.Based on a knowledge base, the link between particular variables is stated (theory).Each variable specifically served as a latent variable for a theoretical idea.PLS was helpful in mapping all possible routes to several dependent variables using a comparable research methodology.Additionally, it was essential to evaluate all directions in the structural model.[39].

III. RESULT AND DISCUSSION
Table 1 shows the respondents' characteristics, specifically 104 and 102 men and women.It involved students and private employee respondents with 36, 52, 79, 26, and 13 from the Accounting, Management, Information System, Industrial Engineering, and Computer Science study programs from Indonesia's top three distance learning universities.Most students (134) access the learning management system (LMS) from 1 to 3 hours, 47 less than 1 hour, and 25 more than 3 hours per day.
The convergent validity test shown in Table II demonstrates the strong correlation value shared by all indicators.The P-value is less than 0.05, and the loading coefficient value is significant at or above 0.60.As a result, using the loading factor approach, the apparatus or questionnaire was created to have strong convergent validity.In the cross-loading test, the indicator load value is compared to its latent variable as well as other latent variables.For this cross-load test, it is acceptable if the loadrelated p-value is 0.05 and the load factor is 0.70, or between ranges of 0.60 to 0.70 [40].The correlation loads between each indicator and the latent variables that have a larger value than the other variables are shown in Table III.Cross-loading is the basis for the instrument or questionnaire discriminant validity.After examining the convergence and discriminant of validity, the reliability test was carried out on each component.The R-squared factor, composite reliability (CR), Cronbach's Alpha, and AVE scores are a few of the reliability test's components.Cronbach's alpha ( 0.50), combined reliability (CR) (> 0.70), and the AVE value of the reliability ( 0.50) are used to describe the reliable components of the search.A setup with a trustworthy questionnaire and an AVE value of at least 0.5 can account for more than 50% of the variance [41].The findings and parameter values for each observable (indicator), external latent, and internal variable are shown in detail in Fig. 2, along with the impacts of each variable as shown by the path factor and p-value.The latent predictors and norms are represented in columns and rows.
Student Engagement before mediation through satisfaction with a p-value of 0.000 (less than 0.05) is directly influenced by Information, System, and Service Qualities.However, the indirect effect between Service Quality with a p-value of 0.000 (less than 0.05) was also significant.Therefore, Student Engagement is indirectly influenced by Service Quality.Indirect impacts of Information and System Qualities are insignificant to the Student Engagement mediated by students' satisfaction with a p-value of 0.111 and 0.112 (≥0.05).Students become more skillful at managing complexity, tolerating ambiguity, and working with people with different opinions.Beneficial educational activities help in skills and attitude development for a better future.Effective communication from the lecturers helps to improve student concentration.Higher education should promote effective system organization, monitor students learning progress, respect them, and accurately evaluate their work.
The need to create and build courses before the actual distribution of the material will help to improve online course distribution.Teacher-student interaction, curriculum structure, communication, and lecture attendance lead to effective class implementation [42].Furthermore, teachers' active learning practices lengthen students' concentration [43].Specifically, students will be more interested and participate in the learning process.
Students are engaged to thrive and grow due to teacher efforts and performance, creating an engaging experience.The teacher performance is distributed along with the learning in the system.It has been proven that student progress is influenced by the teacher's personality, expertise, evaluation tools, and other factors and the classroom environment.

IV. CONCLUSION
The study analyzed the factors that influenced student satisfaction and engagement.Quality learning is significantly affected by students' satisfaction.Therefore, evaluation is necessary to measure the effectiveness of online learning, including increased knowledge, skills, and development positive attitudes.Exams can be used to measure the knowledge level in students, including quizzes, structured tasks, mid and final tests.The satisfaction with using elearning is evidenced through the process.According to students, online learning is less supportive in the teaching and learning process.Therefore, groups should facilitate them to promote interaction and a conducive learning environment.
Conclusively, System, Information, and Service Qualities significantly affect Student Satisfaction.
It is easy to use the system when provided with an orientation about the program and technical matters using KMS features.This orientation could prepare students to participate in the existing system's learning process actively.Program flexibility should accommodate students' context and conditions while accessing materials, participating in discussions, and submitting assignments.Furthermore, online program organizers and developer lecturers should understand online pedagogy.Participants actively interact with students, lecturers, and materials through online programs.
There is a need to design various activities and assignments to have an interactive and active learning environment in online programs.Moreover, role-playing and case studies commonly used during physical learning help to promote interaction and are packaged in online programs using media and communication at different times (asynchronous) and simultaneously (synchronous).University officials must address this problem through gamification by providing more interactive educational content in various formats, such as video clips.Also, providing an interactive graphical interface will serve as a viable tool for engaging students, ultimately contributing to their intention to continue learning.However, System, Information, and Service Quality significantly affect Student Engagement.

Fig. 2
Fig. 2 Conceptual Framework Mediation occurred when the third mediating variable interfered with the other two related components.The intermediate test results are illustrated in Table VI.

Table V
is an example of a path coefficient test comparing configurations to verify the magnitude and force of the impact and test the hypothesis.The hypothesis was supported if T-Statistics were greater than 1.96 (alpha = 5%).The findings of the hypothesis test and the comments are presented in TableIII.

TABLE VI MEDIATION TEST Through Student Satisfaction Indirect Effect P- Values for Indirect Effect Direct Effect P- Values for Direct Effect Total Effect P- Values for Total
System Quality, IQ -Information Quality, SQ -Service Quality, SK -Skill, Par -Participation, SAT -Satisfaction