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All Journal Journal of Educational Sciences International Journal of Technology and Modeling
Dewi Anita Sari, Dewi Anita
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Religion Humanities Computer Science & IT Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Other

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The Influence of the Guided Inquiry Learning Model on Students' Critical Thinking Skills in Fisheries Subjects in Grade IV of SD Inpres 2 Besusu Nuraini, Nuraini; Sari, Dewi Anita; Zulnuraini, Zulnuraini; Aras, Nurul Fitriah; Khairunnisa, Khairunnisa
Journal of Educational Sciences Vol. 9 No. 5 (2025): Journal of Educational Sciences
Publisher : FKIP - Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jes.9.5.p.4695-4706

Abstract

This study aims to analyze the learning outcomes of students whose learning uses the Guided Inquiry learning model on students' critical thinking skills in the science course in grade IV of SD Inpres 2 Besusu. This study uses a quantitative approach with a pre-experimental experimental design in the form of a pretest-postest design for one group. Sampling was carried out using a random sample extraction technique. The data collection technique uses learning outcome tests, observation sheets and interviews. The data analysis used in this study is descriptive and face-to-face statistical analysis. Based on the results of a study on the Influence of the Guided Inquiry Learning Model on the Critical Thinking Ability of Social Science Students of Grade IV SD Inpres 2 Besusu on the Influence of Social Science Learning Outcomes of Students of SD Inpres 2 Besusu on the Influence of Social Science Learning Outcomes of Students of SD Inpres 2 Besusu Class IV, the researcher can draw the conclusion that there is an influence of the use of the Guided Inquiry learning model on the influence of learning outcomes Social Studies Students Grade IV SD Inpres 2 Besusu.
Towards Efficient Crowd Counting and Behavior Analysis Using YOLOv11 Lubis, Amanda Amalia; Prasasta, Adrian; Sari, Dewi Anita
International Journal of Technology and Modeling Vol. 4 No. 1 (2025)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v4i1.128

Abstract

The rapid growth of urban populations has intensified the need for robust crowd monitoring systems to ensure public safety and efficient resource management. This study explores the integration of YOLOv11, an advanced real-time object detection model, for crowd counting and behavior analysis in dynamic environments. We propose a hybrid framework that leverages YOLOv11’s high-speed detection capabilities to identify individuals in densely packed scenes and extract behavioral cues such as motion patterns and group interactions. The model is fine-tuned on benchmark datasets to optimize accuracy in varying lighting and occlusion conditions. Experimental results demonstrate that our approach achieves a significant improvement in both counting precision and behavioral feature extraction compared to previous YOLO versions and other baseline models. This research highlights YOLOv11’s potential as a lightweight yet powerful solution for real-time crowd analytics, with applications ranging from smart surveillance to public event management.
Co-Authors Khairunnisa Khairunnisa Lubis, Amanda Amalia Nuraini Nuraini Nurul Fitriah Aras Prasasta, Adrian Zulnuraini