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Jurnal Ilmu PendidikanJurnal Ilmu Pendidikan

This study aims to analyze students conceptual understanding of the Aviation Security (AVSEC) course, focusing on the topic of Perimeter Intruder Detection System (PIDS) using the Science, Technology, Engineering, and Mathematics (STEM) approach. This study uses a quasi-experimental design with pre-test and post-test approaches to evaluate the effectiveness of STEM approaches in improving students conceptual understanding. A total of 25 cadets from the MTU study program, Surabaya Aviation Polytechnic, became the subject of the research. The instruments used include conceptual comprehension tests, observation sheets, questionnaires, and in-depth interviews. The results of data analysis using the Paired Sample T-Test showed that there was a significant increase in student understanding after the application of STEM methods. The average value of the difference between the pre-test and the post-test was -17.750 with a standard deviation of 4.665, and a significance level of 0.000, indicating a significant increase in understanding. The 95% confidence interval for the mean difference is between -19,720 to -15,780. The PIDS system was developed using the Research and Development (R&D) method, while the development of hardware and software followed the Waterfall approach. The results of this research make an important contribution to the development of STEM-based learning methods in the field of aviation safety, especially on the topic of PIDS.

The application of the Science, Technology, Engineering, and Mathematics (STEM) approach significantly improves students conceptual understanding of Perimeter Intruder Detection Systems (PIDS) in the Aviation Security (AVSEC) course.The Paired Sample T-Test results demonstrated a significant improvement in student understanding after STEM-based learning, with a statistically significant difference between pre- and post-test scores.This research contributes to the development of STEM-based learning methods in aviation safety, particularly in PIDS.

Further research could explore the integration of artificial intelligence (AI) and machine learning algorithms into the PIDS system to enhance its accuracy and reduce false alarms, potentially leading to a more proactive and intelligent security system. Additionally, investigating the effectiveness of virtual reality (VR) or augmented reality (AR) simulations in training AVSEC personnel on PIDS operation and response protocols could provide a more immersive and practical learning experience. Finally, a comparative study examining the cost-effectiveness of different PIDS technologies, including those utilizing IoT and advanced sensor networks, would be valuable for optimizing resource allocation and maximizing security effectiveness in airport environments. These investigations should focus on real-world implementation challenges and consider the scalability and adaptability of these technologies to various airport sizes and security needs, ultimately contributing to a more robust and resilient aviation security infrastructure.

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