Sunday Emmanuel Fadugba
Ekiti State University

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Optimization of Flood Detection Systems Using Hybrid BP-TRQN Neural Network Algorithms: An In-Depth Review Syaharuddin; Saba Mehmood; Wasim Raza; Sunday Emmanuel Fadugba
Joutica Vol 11 No 02 (2026): SEPTEMBER
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jti.v11i02.1648

Abstract

accurate, stable, and efficient real-time detection system. The purpose of this study is to conduct a Systematic Literature Review of the performance of the Hybrid Back Propagation–Time Recurrent Quantum Networks (BP-TRQN) algorithm in optimizing accuracy, learning stability, and data processing efficiency in flood detection systems. This study employed the PRISMA-based Systematic Literature Review (SLR) method to identify, screen, and analyze relevant studies. A total of 44 articles published between 2015 and 2025 were selected from the Scopus, DOAJ, and Google Scholar databases based on predefined inclusion and exclusion criteria. The results show that Hybrid BP-TRQN consistently provides significant improvements over single models, particularly in reducing Root Mean Squared Error (RMSE), increasing the coefficient of determination (R²), and accelerating convergence. The integration of temporal and spatial components and optimization has been proven to strengthen the model's ability to process large-scale hydrometeorological data and satellite images more adaptively. In addition, the application of hybrid algorithms also improves computational efficiency, making it potentially applicable in real-time early warning systems. Thus, BP-TRQN can be considered a promising approach in supporting flood disaster mitigation through a more reliable and responsive detection system.
The Effect of Digital Fatigue and Emotional Regulation on Mathematical Problem-Solving Skills Istikatunisah; Syaharuddin; Abdillah; Wasim Raza; Sunday Emmanuel Fadugba
Formatif : Jurnal Ilmiah Pendidikan MIPA Vol. 16 No. 1 (2026): Formatif: Jurnal Ilmiah Pendidikan MIPA
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/formatif.v16i1.1990

Abstract

Mathematical problem-solving skills are an important component of mathematics learning because they require concentration, accuracy, and emotional control. In technology-based learning environments, intensive use of digital devices may lead to digital fatigue, which can reduce students’ focus, while emotional regulation is considered an important factor that helps students maintain cognitive stability during learning. This study aimed to examine the effect of digital fatigue and emotional regulation on students’ mathematical problem-solving skills. The study employed a quantitative approach with a correlational research design. The sample consisted of 34 eleventh-grade students selected using a total sampling technique. Data on digital fatigue and emotional regulation were collected using Likert-scale questionnaires, while mathematical problem-solving skills were measured through descriptive test items. The data were analyzed using multiple linear regression after meeting the required statistical assumptions. The results showed that digital fatigue and emotional regulation did not have a significant effect on students’ mathematical problem-solving skills. The R² value of 0.023 indicates that the two variables explain only 2.3% of the variance in problem-solving skills. This result may be due to the fact that mathematical problem-solving is more strongly influenced by cognitive factors such as conceptual understanding, reasoning ability, and learning strategies rather than psychological fatigue factors alone. Therefore, future research is recommended to include additional variables such as learning motivation, cognitive strategies, and instructional quality. Practically, teachers are encouraged to strengthen conceptual understanding and problem-solving strategies while maintaining students’ psychological well-being in digital learning environments.