Rezki Aulia
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Penerapan Metode Regresi Linear Berganda Dalam Memprediksi Laju Pertumbuhan Penduduk Kota Pekanbaru Rezki Aulia; Marpaung, Noveri Lysbetty
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 2 (2024): June 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.16.2.2024.137-147

Abstract

Population growth is a phenomenon with significant implications for the development of a region. Action is needed to anticipate this rapid population growth, one of which is by predicting the population. This study aims to apply Multiple Linear Regression method to predict the population growth rate in Pekanbaru City. The variables of births, male population, and female population are used as predictors in the regression model. Optimization is performed using the Gradient Descent method to improve prediction accuracy. Historical data from 2003 to 2022 is used to train and test the model. The evaluation results show that the optimized multiple linear regression model is able to provide accurate predictions, with a MAPE of 1.09% and RMSE of 0.20618. Further development can be done by considering additional factors and using more advanced optimization methods to improve prediction accuracy. This research is expected to contribute to understanding the factors influencing urban population growth and provide a basis for more effective and sustainable urban development planning.
Design of a VR-Based Virtual Laboratory for Network Practicum: The Effect of Immersion on Learning Outcomes Nurpadhillah Junaid; Ramdan Muaqib; Ramdani; Ratu Balgis Nur Latif; Rezki Aulia
Information Technology Education Journal Vol. 3, No. 3, September (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i3.2401

Abstract

Purpose – This study aims to design and develop a Virtual Reality (VR)-based virtual laboratory for networking practicum and examine the effect of immersion on students’ learning outcomes. Traditional networking laboratories face limitations in infrastructure, accessibility, and scalability, while conventional desktop-based simulations lack immersive interaction. This study argues that immersive VR environments significantly enhance learning performance in networking practicum. Design/methods/approach – A quasi-experimental non-equivalent control group pretest–posttest design was employed involving 62 undergraduate students (32 experimental, 30 control). The experimental group used a VR-based networking lab developed using Unity and Meta Quest 2, while the control group used a conventional 2D simulator. Learning outcomes were measured using a validated 25-item test. Immersion was assessed using the Igroup Presence Questionnaire (IPQ). Data were analyzed using paired and independent samples t-tests, Pearson correlation, and regression analysis (α = 0.05). Findings – The experimental group achieved a significantly higher posttest mean score (M = 82.63, SD = 6.84) compared to the control group (M = 72.14, SD = 7.26), t(60) = 6.02, p < 0.001, with a large effect size (d = 1.48). Immersion showed a strong positive correlation with learning outcomes (r = 0.67, p < 0.001) and explained 45% of variance in posttest scores (R² = 0.45). Research implications/limitations – The study was limited to one institution, a moderate sample size, and short intervention duration, which may affect generalizability. Originality/value – This study provides empirical evidence of the pedagogical effectiveness of immersive VR in networking practicum and demonstrates the significant role of immersion in improving learning outcomes