Research Article
Accuracy of Computational Modeling in Introductory Mechanical Wave Interference
@INPROCEEDINGS{10.4108/eai.17-9-2024.2352889, author={Wawan Bunawan and Pardomuan Sitompul and Tuti Hardianti and Sabani Sabani and Irham Ramadhani and Ummil Khairiyah Siregar and Dinda Farida and Nadira Asha Shakila and Hikma Aini and Anggi Nurjanah}, title={Accuracy of Computational Modeling in Introductory Mechanical Wave Interference}, proceedings={Proceedings of the 6th International Conference on Innovation in Education, Science, and Culture, ICIESC 2024, 17 September 2024, Medan, Indonesia}, publisher={EAI}, proceedings_a={ICIESC}, year={2025}, month={1}, keywords={computational; modeling; mechanical wave; interference}, doi={10.4108/eai.17-9-2024.2352889} }- Wawan Bunawan
Pardomuan Sitompul
Tuti Hardianti
Sabani Sabani
Irham Ramadhani
Ummil Khairiyah Siregar
Dinda Farida
Nadira Asha Shakila
Hikma Aini
Anggi Nurjanah
Year: 2025
Accuracy of Computational Modeling in Introductory Mechanical Wave Interference
ICIESC
EAI
DOI: 10.4108/eai.17-9-2024.2352889
Abstract
Nearly all aspects of research in physics involve the use of computers and are invaluable in laboratory and theoretical research. Even though it is very important as a scientific discipline, the integration of computing into physics learning is still a challenge, especially regarding the ability to construct solutions to physics problems. A very important issue is how to assess the computational modeling of mechanical wave interference patterns. The expansion of computing in learning at least requires a computational model that can show a comparison between analytical problem-solving models and computational modeling. It is necessary to carry out computational modeling assessments and analytical manual solutions. The assessment standard uses a critical value of interference wave amplitude between manual analysis and computational modeling. The creation of computational models provides standardized operationalization of mechanical wave interference problem solving that can be repeated with a higher level of accuracy than manual methods.
