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p-Index From 2021 - 2026
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All Journal Bulletin of Electrical Engineering and Informatics International Journal of New Media Technology
Muhammad Fakhrurrifqi
Universitas Gadjah Mada
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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"Stay at Home Reservation": Langkah Mitigasi dalam Pandemi Covid-19 Faridiah Aghadiati Fajri; Muhammad Fakhrurrifqi; Dian Budi Santoso; Radhian Krisnaputra
IJNMT (International Journal of New Media Technology) Vol 8 No 1 (2021): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v8i1.1837

Abstract

The Covid-19 pandemic condition that has hit the world has had a significant impact on various sectors. Health facilities need information system support in their services. Breaking the distribution chain can be done by maintaining a physical distance. However, in reality, people are still indifferent. There is a possibility that the patient is infected but shows no symptoms or is lying to the point of endangering medical personnel. In addition, there is a stigma in the community so that they are afraid to go to health facilities. Even though it cannot be denied that in certain conditions patients should still have their conditions checked by a doctor. The development of this online registration system aims to reduce the risk of contact between patients and medical personnel. The real-time queue monitoring feature helps patients to wait in line anywhere, so they are not in the patient's waiting room. This system is able to provide real-time queues for examinations in all polyclinics. This can reduce public anxiety about coming to health facilities. Index Terms— Covid-19; Health Facilities; Online Reservation; Pandemic; Realtime Queues
Forecasting graduate student enrollment in university using regression analysis Anggraini Dwiansyah; Imam Fahrurrozi; Muhammad Fakhrurrifqi; Umar Farooq; Ganjar Alfian
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.9713

Abstract

The government ensures educational quality in universities through a quality assurance (QA) system implemented via accreditation, which evaluates both study programs and institutions. A key concern in accreditation is the decline in new student enrollment, making accurate predictions of enrollment numbers essential for quality assessment. This study proposes a linear regression (LR) model to forecast future university student enrollments based on enrollment figures from the previous year as input feature. Using a dataset from one of Indonesia’s leading university spanning 2013 to 2023, the experimental results demonstrate that the LR model outperforms other regression techniques, including multi-layer perceptron (MLP), K-nearest neighbors (KNN), decision tree (DT), and random forest (RF). The LR model achieves R² values between 0.87 and 0.95, reflecting a strong linear relationship between current and future student numbers. It also delivers high accuracy, with root mean square error (RMSE) values ranging from 11.72 to 41.21 per year. The trained LR model has been integrated into a web-based system, offering data visualization and enrollment predictions to support university management in monitoring quality, addressing enrollment challenges, and facilitating informed decision-making.
Co-Authors Anggraini Dwiansyah Dian Budi Santoso Fajri, Faridiah Aghadiati Ganjar Alfian Imam Fahrurrozi Radhian Krisnaputra Umar Farooq