
Friction Force on An Inclined Plane (FFIP) is one of the important chpaters in physics courses. This study aims to develop and determine the performance of the lab physics lab based on the Internet of Things (IoT). This research method uses qualitative method and experimental approach. This physics lab is afterward compared to theoretical calculations from the FFIP formula by using tests at 3 inclined plane’s angles of 30o, 45o, and 60o, as well as at 2 distances of 40 cm and 70 cm. The data were analyzed using ANOVA of simple linear regression to obtain the level of accuracy and the relationship between the inclined plane’s angles and the distance towards the kinetic friction coefficient of the test objects. The results of the study shows that the development of the lab physics FFIP IoT-based has very decent performance as long as the error percentage (average) is 4.77% or less than 10% as well as the level of accuracy (average) is 95.23%. The results of the analysis showed that the inclined plane’s angles have a significant effect towards the kinetic friction coefficient of the test objects. On the other hand, the distance barely has no effect towards the kinetic friction coefficient.
level of accuracy, ANOVA, Physics lab, internet of things, kinetic friction coefficient
level of accuracy, ANOVA, Physics lab, internet of things, kinetic friction coefficient
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
