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Predicting student performance in higher education using multi-regression models Leo Willyanto Santoso; Yulia Yulia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.14802

Abstract

Supporting the goal of higher education to produce graduation who will be a professional leader is a crucial. Most of universities implement intelligent information system (IIS) to support in achieving their vision and mission. One of the features of IIS is student performance prediction. By implementing data mining model in IIS, this feature could precisely predict the student’ grade for their enrolled subjects. Moreover, it can recognize at-risk students and allow top educational management to take educative interventions in order to succeed academically. In this research, multi-regression model was proposed to build model for every student. In our model, learning management system (LMS) activity logs were computed. Based on the testing result on big students datasets, courses, and activities indicates that these models could improve the accuracy of prediction model by over 15%.
Realistic influence maximization based on followers score and engagement grade on instagram Kristo Radion Purba; Yulia Yulia
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2656

Abstract

In recent years, the emergence of social media influencers attracts the study of a realistic influence maximization (IM) technique. The theoretical performance of IM has become matured. However, it is not enough since IM has to be implemented in a social media environment. Realistic IM algorithms and diffusion models have been proposed, such as the addition of user factors or a learning agent. However, most studies still relied on the influence spread benchmark, which makes the usefulness questionable. This research is among the first IM study using Instagram data. In this study, two diffusion models are proposed, which are based on the original IC and LT models, with the addition of the engagement grade (EG) factor. An algorithm called IMFS (IM with followers score) is proposed to accommodate the new models as well as IC and LT. In addition, realistic benchmark methods are proposed, namely the average engagement of the activated users, and the overlapping between post likers and activated users. The result shows that the proposed models are 2-3x more realistic if compared to IC and LT.
Business Process Simulation Game as a Business Process Learning Tool for Retail Companies Joella Joella; Yulia Yulia; Andreas Handojo
International Journal of Industrial Research and Applied Engineering Vol 5, No 2: OCTOBER 2020
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jirae.5.2.33-40

Abstract

Game-based Learning has become one of the most developed learning methods in this 21st century. Game-based Learning is a good learning method because it can create a virtual world where players can simulate real-world problem-solving. A business process is a series of interrelated activities to achieve certain business goals, executed sequentially or parallel, both inside and outside the company. The complexity of business processes causes the learning process to be less than optimal, if only in the form of theoretical exposure. Practices are needed to hone students’ business process management skills, which will be too risky to be done in the real world.  Therefore, this research develops a business process simulation game to facilitate students in practicing their business process management skills. The author analyzed the existing business process simulation games, determined the game system design, developed the game, tested the game, and distributed questionnaires to users. Based on the results of testing and implementing the system that has been done, the game developed in this research has a positive impact on users. The features in the game are running well and as expected. The game provides benefits to both teachers and students, so this game is suitable for being used as retail companies' business process learning tool