Publication Search

Analysis of E-Learning Information Systems is certainly one of the efforts that can be made to overcome problems that arise in the process of implementing teaching and learning activities (KBM) in each school. Soft System Methodology (SSM) analysis is a method used to help model unstructured problems. The SSM methodology is suitable for assisting an organization in defining their goals and then building a human activity system to achieve those goals. The relationship between the internal and external academic community involves teachers, parents of students, students and school administrators to develop information for supervision and student Development approaches. E-Learning analysis using the Soft Systems Methodology (SSM) approach is expected that the E-Learning information system will be able to answer existing challenges and problems. This study carried out a CATWOE analysis of the holons and elements (Client, Actor, Transformation, World View, Owner, Environment) found in case studies, building E-Learning models by applying the roles of humans, processes and technology as knowledge-forming elements, then analysis. holons based on the modeling of the resulting Knowledge. The analysis of E-Learning needs is answered by the need between the internal staff of teachers, employees, counseling and external students and parents to improve the quality of teaching and learning activities and student development.

Stikubank University (Unisbank) Semarang has implemented a web-based learning system known as a smart campus in which there is an integrated smart campus e-learning model. E-learning applied by Unisbank management is an online learning medium by utilizing information technology to make it easy for all students and lecturers to use in the teaching and learning process. This study aims to analyze the success of university e-learning based on the adaptation of the Delone and McLean information system success model. Primary data and secondary data were used in this study, a questionnaire instrument was used to obtain primary data. Furthermore, the data is processed quantitatively using the Smart PLS 3.0 software. The results of the data test were then analyzed descriptively to provide a narrative description of the research results. The results of research data processing showed that (1) Student assessment of system quality in the e-learning system had no significant effect on intention to use with a p-value of 0.729; (2) Student assessment of system quality in the e-learning system has a significant effect on user satisfaction with a p-value of 0.002; (3) Student assessment of information quality in the e-learning system has a significant effect on intention to use with a p-value of 0.025; (4) Student assessment of information quality in the e-learning system will have a significant effect on user satisfaction with a p-value of 0.000; (5) Student assessment of service quality in the e-learning system has no significant effect on intention to use with a p-value of 0.166; (6) Student assessment of service quality in the e-learning system will have a significant effect on user satisfaction with a p-value of 0.000; (7) User satisfaction related to the e-learning system has a significant effect on intention to use with a p-value of 0.000; (8) Intention to use e-learning system has a significant effect on net benefits p-value 0.004; (9) User satisfaction in the e-learning system has a significant effect on net benefits with a p-value of 0.000. Keywords: PLS, SEM, SmartPLS 3.0, E-Learning, Information Systems success, Delone & McLean Model.