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Arduino-Based High-Frequency Signal Data Acquisition for Learning Media on Antenna and Wave Propagation Practices
Masduki Zakarijah, Department of Electronics and Informatics Engineering Education Faculty of Engineering Yogyakarta State University, Indonesia
Nikko Aji Bayu Nugraha, Department of Electronics and Informatics Engineering Education Faculty of Engineering Yogyakarta State University, Indonesia
Abstract
This paper discusses the research results on the development of learning media and the results of the feasibility test for the learning process. This study aims to: (1) obtain the design and prototype of Arduino-based high-frequency signal data acquisition learning media; (2) find out the level of feasibility of learning media that has been made for the learning process of Antenna Practice and Wave Propagation courses. The research model uses Research and Development with the ADDIE development method. The research stages in the ADDIE method are Analyze, Design, Develop, Implement, and Evaluate. The research began with the development of learning media called Antenna Pattern Radiation Learning Media and the Practicum Module containing a collection of lab sheets for practicum activities using the media. The next step involves assessing the viability of the media. Validation tests gather expert feedback on materials, media, and users. In this study, data was collected using a questionnaire and analyzed quantitatively using descriptive analysis techniques. This research and development effort led to the creation of Antenna Pattern Radiation Learning Media and its practical modules. The test results showed that the material experts gave it a score of 95%, media experts rated it at 85.4%, and users (students) gave it a score of 80.65%. Based on the evaluations of the material experts, media experts, and users, it can be concluded that the Antenna Pattern Radiation learning media falls into the highly feasible category and can be utilized as a learning resource in courses related to Antenna and Wave Propagation.
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DOI: https://doi.org/10.21831/elinvo.v8i1.60182
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