DEVELOPING A VISCOSITY PRACTICUM TOOL BASED ON INTERNET OF THINGS (IOT) TECHNOLOGY IN THE IMPLEMENTATION OF HYBRID LEARNING PHYSICS

• Main Author: Hilal Sudarbi, Muhammad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/70623
• Institution: Institut Teknologi Bandung

Concepts and theories in physics that are studied directly can be more meaningful. However, the COVID-19 pandemic has limited real interaction and communication. So there needs to be a combination of face-to-face learning and online/computer-based learning. Learning with Hybrid Learning methods assisted by Internet of Things (IoT) technology makes this possible. This study aims to 1) produce a viscosity practicum tool based on Internet of Things (IoT) technology in the implementation of Hybrid Learning Physics. and 2) to determine the feasibility level of the viscosity practicum tool based on Internet of Things (IoT) technology in the implementation of Hybrid Learning Physics. This research was a research and development approach (R & D) by adapting the Alessi and Trollip development model that is: (1) planning, (2) design, and (3) development. The trial design uses media and materials experts. The product produced in this study is an Internet of Things (IoT)-based viscosity practice tool that will be used in learning that has been tested and has been assessed for feasibility by media experts and material experts. With a material feasibility level of 87% and a media feasibility level of 90%, this instrument is viable enough to be employed in the physics learning process, according to its validation results. This development will emphasize the use of IoT as a learning tool. The type of media developed is practicum media and practicum modules in the form of a website that can be viewed online from anywhere without the need to be physically present in the laboratory, so as to make the practicum learning process more realistic and enable easier access. To evaluate the accuracy of the proposed viscosity practicum tool, experiments were conducted by altering the size and material of balls in three different colored liquids. The viscosity of the blue liquid was determined to be 16,40695 poise, the viscosity of the clear liquid to be 12,25698 poise, and the viscosity of the yellow liquid to be 13,25525 poise. While laboratory tests determined the viscosity of blue liquid to be 16,44916 poise, clear liquid to be 12,25580 poise, and yellow liquid to be 13,27682 poise. Based on these calculations, the difference between the video analysis and real viscosity value for the blue liquid is 0,09328 poise, for the clear liquid it is 0,04638 poise, and for the yellow liquid it is 0,06065 poise. For the blue liquid, the discrepancy between the viscosity practicum tool and the real viscosity value is 0,04221 poise, for the clear liquid it is 0,00118 poise, and for the yellow liquid it is 0,02157 poise. Visibly, the viscosity value difference between the viscosity practicum tool and the real viscosity value is smaller than the viscosity value difference between the video analysis and the actual viscosity value. This demonstrates that the IoT-based viscosity practicum tool is highly precise.