Keywords: E-Learning, Higher Education, Service Quality, Customer Satisfaction, University Image.

INTRODUCTION

Over the globe, there is a long series of very deadly outbreaks. A pandemic is a rapidly spreading infection epidemic that increases disease risk and induces significant economic, social, and political damage (Madhav et al., 2017; Wang et al., 2008; Taylor, 2019). Evidence suggests that globalization, urbanization, and overexploitation of natural and environmental resources have also raised the possibility of a pandemic. The Disease outbreak, which started in Wuhan, China, has nearly fully spread across the world. There are about 200 countries, including Indonesia. The pandemic's effects triggered crises in several fields, including health, education, and the environment (Karabag, 2020; Ozili, 2020;).

The effect of the Covid-19 spread has now started to reach the world of education (Onyema, 2020). Educational organizations are not expected to perform their regular procedures, which is expected to limit the distribution of Covid-19. The spread of the Coronavirus will occur via communication with individuals (via touch, saliva, etc.), so many countries around the world ask their people to practice social and even physical distance to prevent the dissemination of Covid-19 (Abel et al., 2020; Luiggi-Hernández & Rivera-Amador, 2020). As a result, areas where large gatherings and physical interaction are permitted, such as classrooms, universities, and other educational facilities, must be closed. According to UNESCO, the Covid-19 pandemic affects 577,305,660 students from elementary to secondary school and 86,034,287 students from higher education worldwide. Indonesia, like other countries afflicted by the Covid-19 outbreak, has suspended all educational programs. As a result, the government and associated institutions offer an alternate educational process for pupils, such as distance learning, online learning, or learning from home (Purwanto et al., 2020; Rokhani, 2020; Engko & Usmani, 2020). Colleges and schools are only physically closed, in the sense that school facilities and campuses are closed, but academic events and other routine activities have to be carried out electronically. Teachers and lecturers continue to teach online, while teachers and students can study online from the convenience of their own homes (e-learning) (Sterpetti, 2020; Agarwal & Kaushik, 2020; Wiliamson et al., 2020).

LITERATURE REVIEW

E_Learning

Bullen & Janes (2007) define e-learning as learning that occurs when internet technology facilitates, conveys, and enables the learning process over long distances. A more general definition put forward by Freire et al. (2008), namely E-learning, is the use of interactive means to learn in instructional or training programs. According to Naidu (2006), "e-learning is widely defined as the deliberate use of networked information and communications technologies in teaching and learning." A computer network is one of the media that is used. As a consequence, it is possible to build in web form. Web-based e-learning presentations will be more immersive. Real-time information about lectures is also possible. Similarly, though not face-to-face, seminar discussion boards can be done online and in real-time. Since the e-learning system does not have entry limits, seminars may be held for a more extended period. Students can use this device whenever and anywhere they want as long as there is an internet connection (Husaini, 2017; Aziz, 2013). E-learning activities can be classified according to the time of learning (Clark & Mayer), namely:

a. Synchronous e-learning where educators and students are involved in learning activities simultaneously, for example, video conferencing, chatting, and real-time video.

b. Asynchronous e-learning where educators and educators are involved in learning activities at different times, for example: by sending/providing teaching materials, activities in forums, blogs, or wikis, via email and file sharing.

The lack of e-Learning delivery in general, rather than concerns with resources, applications, or technology, should be a source of concern when introducing e-learning in education. However, this is mainly due to human factors, such as the magnitude of changes in work culture and a lack of desire to share information (Weaver, 2016; Qureshi et al., 2012; Jones & O'shea, 2004). To obtain the desired results in implementing e-learning in education, you must pay attention to the following matters:

a. E-Learning must be designed to be able to provide added value formally and informally for users.

b. Apply blended learning first during the socialization period to train users in e-life style.

c. The e-Learning project is an institutional initiative and not just an HRD initiative

d. Make users the main role (support user self-actualization), not just objects.

Student retention is the primary metric used to assess the success of higher education websites. Student happiness is critical for all educational institutions to achieve their benefits by developing and sustaining student behaviors and behavioral intentions (Suki, 2013; Szymanski & Henard, 2001). According to Yilmaz, there are two forms of satisfaction: cognitive satisfaction and successful satisfaction (2017). Student successful satisfaction occurs when the exact nature of the information and expertise gained is what the students perceive and positively impact student mindset (Dominici & Palumbo, 2013). This successful satisfaction will minimize e-learning cases and harm the institution's credibility, such as in the Coronavirus lockout, where multiple universities participate in online learning, which can affect student satisfaction and the institution's reputation. Successful e-learning, on the other hand, has a favorable influence on student satisfaction rate, and this analysis proposes the following hypothesis:

H1: Student e-learning has a positive relationship with student satisfaction.

Service Quality

According to Kotler and Keller (2006), service is "any intangible act or performance that one entity provides to another that does not result in possession of something." In other terms, service can be described as a non-ownership contract for services made by one party to another. According to him, quality is a characteristic of goods or services used to meet specific needs. Quality is closely related to markets. Therefore the word quality implies particular requirements according to what customers expect. Lovelock & Wright (2002) argues that service is an economic activity that creates and benefits customers at certain times. In other words, service is an action tailored to the needs of service users. According to Kotler (2003), service is described as an operation performed by one party to another. As a result, the critical service orientation is customer loyalty. According to some of these experts' concepts, service efficiency is the entirety of the features of a service geared toward satisfying consumer needs. This is in line with what was stated by Parasuraman et al. (1985), which defines service quality as a "global evaluation or attitude of the overall excellence of services." Customer evaluation of a product (both goods and services) will determine whether the product used has. According to Parasuraman, the concept of service quality has given a color whether it is relatively the same as the expectation paradigm developed in satisfaction research. In the study, Parasuraman et al. Measured customer expectations in service companies, namely customer trust in service companies compared to perceptions of the reality of the services received. The most important aspect of student e-learning is website services' efficiency (Chopra et al., 2019). Even though websites' quality is low, several studies have been conducted to investigate the association between website quality and student academic performance. According to the qualitative literature on web-based educational practices, website accessibility is related to student learning requirements, increased curriculum, and the web-based education system is connected to student interest in teaching (Wu & Lin, 2012). Furthermore, its use of internet learning must receive worldwide attention due to the Coronavirus threat, which has caused several educational institutions to switch to online education, affecting student learning. Therefore, an electronic service quality check is required for students' electronic learning, and the following theory is developed as a result of this research:

H2: Electronic Service Quality has a positive effect on Student Satisfaction.

University Brand Image

According to Barich & Kotler (1991), a company's reputation would be high if consumers feel they are having a decent deal when they buy from them. As such, several factors such as good products, services, and reasonable prices can affect value. Company image is also expressed as a function that involves striking attributes, which are evaluated and valued among each other. Therefore, company image or image is defined as a complex consumer perception about a different company. However, different authors have distinguished the company's additional attributes or characteristics from year to year, which are part of the overall corporate image. The appearance of prospective customers, who can influence consumer satisfaction, can trigger a signal of knowledge in a company image. When service characteristics are challenging to determine, the company's reputation impacts customer preference (Nguyen & Le Blanc, 1998). Via contact and practice, a company's brand is created and built to retain customers. It is known that the brand logo has a halo impact on consumer loyalty considerations. Consumers pay attention to different facts about the company or organization and how their experience is with using the company's goods and creating a logo and store profile. As customers have positive encounters with a company's different product brands, they form a favorable opinion of the company (Nguyen, 2006). The university's image has a significant effect on student decision-making. University branding is a sophisticated publicity tool used to keep students motivated, involved and position the school in the competition. According to Azoury et al. (2014), there is a need for university image branding to incorporate image branding strategies in this increasingly competitive period. As a result, the brand represents the university's desire to fulfill student demands, fostering confidence in offering more programs to students (Xiao et al., 2014). However, because of the coronavirus lockout, student satisfaction levels can suffer from online sessions rather than physical classes. Colleges are also delivering online courses to their students, which may affect not just student learning but also their satisfaction with the university's brand name. Thus, this study develops the hypothesis that:

H3: University Brand Image has a positive effect on student satisfaction.

METHOD

This study's research design is quantitative-hypothesis testing research, which is research done by a mechanism that helps researchers build theories and empirically evaluate them. The type of data used in this analysis is quantitative data. This analysis approach uses essential random sampling as the sampling methodology. In this study, 100 private university students in Bandung were used as respondents. The questionnaire is intended to be closed, except for questions or comments about the respondents' personalities Methods for data analysis of PLS and SmartPLS 3.0 and the desktop edition as a tool (Ghozali, 2014).

RESULT AND DISCUSSION

Convergent and discriminant validity checking is part of the estimation model analysis process. In the meantime, Cronbach's alpha and composite reliability were used to assess build reliability. The PLS research results will be used to validate the test hypothesis if any of the parameters in the PLS model meet the convergent validity, discriminant validity, and reliability checking criteria. The loading factor of each predictor against the build is used in the concurrent validity evaluation.

The minimum load factor size limit agreed in this analysis is 0.5, such that the AVE value of each build is greater than 0.5. (Ghozali, 2014). Based on the SmartPLS 3.0 processing results and after deleting indicators or objects that do not meet the criteria, as seen in Figure 2, Currently, both metrics have a loading factor greater than 0.5. As a result, this study model's convergent validity meets the criterion. The loading value, Cronbach's alpha, composite longevity, and AVE for each complete build are shown in Table 1:

Confirmatory factor checking is used to ensure that another latent factor specification is different from another. If each exogenous construct's square AVE value exceeds the relationship between constructs and other constructs, the model has strong discriminant validity.

The Discriminant Validity Test results are seen in Table 2, and both constructs have a square root value of AVE greater than the correlation value with other latent constructs (via Fornell-Larcker criteria). Similarly, as seen in Table 3, the importance of cross-loading all products from an identifier exceeds the other indicator items' cross-loading value, suggesting the formula's discriminant validity (Fornell & Larcker, 1981). Besides, a collinearity test is performed to determine if the model contains collinearity. A VIF measurement is necessary for each build to determine collinearity. The model is collinear if the VIF score exceeds 5 (Hair et al., 2014). Table 3 indicates that all VIF ratings are below 5, suggesting that this model has no collinearity. The composite reliability and the Cronbach alpha value of each build will be used to evaluate create reliability. Cronbach's alpha and recommended composite longevity all surpassed 0.7 (Ghozali, 2014). Table 1 shows that both structures have composite stability and a Cronbach's alpha value greater than or equal to 0.7 (> 0.7). Finally, both constructions met the necessary longevity.

Deep model testing is another term for hypothesis testing in PLS. The impact test was carried out using the SmartPLS 3.0 program and the t-statistic test for the partial least squared (PLS) estimation model. As seen in Table 4, the bootstrapping procedure was used to determine the R Square value and the significance test value.

According to Table 5, the R Square value for Student Satisfaction is 0.873, which means that 87.3 percent of the satisfaction variable can be explained by pictures, satisfaction, and service efficiency.

The Role of E Learning on Student Satisfaction

According to the test results and values in Table 5, Hypothesis 1 (H1) has a beta value of 0.209, SE of 0.021, t coefficient of 3.109, and p-value of 0.001, meaning that Digital learning has a favorable and significant effect on student satisfaction, and thus H1 is acknowledged. According to the findings of this report, there is an impact of online learning on student satisfaction, which means that with a robust E-learning framework, students will choose to study and obtain the skills and degrees they seek, which would, of course, influence student satisfaction. This study's observations are consistent with those of Cole et al. (2014). According to the study's conclusions, online learning affects student satisfaction. Nortvig et al. (2018) obtained research results that E-Learning affects Word of Mouth (WOM), and WOM affects student satisfaction with the college they will choose. So indirectly, E-Learning affects student satisfaction. Dominici & Palumbo (2013), it can be seen that E-Learning is very influential on the quality of students and the quality of students itself dramatically affects the image of the university, which leads to student satisfaction. As a consequence, E-Learning implicitly has a positive and vital impact on Student Satisfaction. So, in general, the H1 hypothesis, namely that E-Learning positively impacts student satisfaction, is acceptable.

The Role of Service Quality on Student Satisfaction

According to the test results and summaries in Table 5, the beta value for Hypothesis 2 (H2) is 0.311, SE 0.043, t coefficient is 3.409, and the p-value is 0.002, implying that service efficiency has a favorable and vital impact on student satisfaction. As a result of which H3 is approved. This shows that improving the quality of information technology services, especially the quality of websites owned by higher education institutions, affects student satisfaction. The COVID-19 pandemic makes universities obliged to conduct online lectures using internet devices or E-Learning. With this learning from home, the tertiary institution must improve services, especially in the technology sector, so students do not feel hampered in their education. The university must begin to aim to boost the level of service in the campus website market, vital to the smooth learning process through E-Learning. With good service, students will be impressed with the service and can be sources of information and reference for other students or other prospective students. The findings of this study are consistent with the results of Nsamba (2019), who found that the efficiency of electronic resources has a significant impact on e-learning student loyalty. Various historical findings have also highlighted that electronic facilities' efficiency positively affects student electronic learning, which is consistent with current research (Martinez-Arguelles et al., 2009; Khodadad Hoseiny et al., 2013). According to Zeglat et al. (2016), electronic resources' consistency must have tangibility, efficiency, responsiveness, and security to facilitate student e-learning. Furthermore, to offer a more robust e-learning environment for students, higher quality electronic content must be provided. The quality of e-information is essential for developing student e-learning systems and motivating students to take advantage of online learning facilities. This will give satisfaction to these students so that indirectly the quality of service affects student satisfaction.

The role of Brand Image on student satisfaction

According to the test findings and summaries in Table 5, the beta value for Hypothesis 3 (H1) is 0.312, SE 0.041, t coefficient is 3.109, and the p-value is 0.001, suggesting that brand image has a favorable and substantial impact on student satisfaction. According to the findings of this report, there is an impact of image on satisfaction, which suggests that students will be happier by enhancing the image of higher education. With good E-learning facilities and the availability of good quality information technology services, students will feel comfortable studying even if they are from a distance. This, of course, will make them convey this to friends or inform the social media they have. This will undoubtedly increase the university's brand image so that indirectly the brand image possessed by each university is very influential on student satisfaction in studying at campus findings of this study are consistent with the findings of Jalilvand and Samiei (2012). They discovered that picture has an impact on consistency. Kim et al. (2000) obtained the study results that the image possessed by a university has a strong influence on Word to Mouth (WOM) from student to student so that it affects satisfaction. So indirectly, the idea of the university affects student satisfaction. Based on this, it can be concluded that the university's brand image has a positive effect on student satisfaction.

CONCLUSION

The results of this study prove that the three hypotheses can be accepted. First, E-Learning gives students satisfaction because even though there is currently a COVID-19 pandemic, they do not feel deprived of the opportunity to study in college. Therefore, private universities in the city of Bandung are competing to improve their ability to implement E-learning on campus to attract students to join. Both the quality of E-Learning information technology services have a positive and significant effect on student satisfaction. The campus with a reliable information technology system to improve E-Learning fluency tends to be chosen by students. The three University Brand Images have a positive influence on student satisfaction. With E Learning learning and the existence of reliable quality information technology services, it will certainly raise the college's image. The advantages they have will make students satisfied to motivate students to refer their campus to friends, relatives, and people through their social media.

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