The development of RBL-STEM learning materials to improve the students’ forecasting skills in solving resolving efficient dominating set for hydroponic farming

Abstract

Students' forecasting skills are currently still very low. This study aims to develop learning tools with the Riset-Based Learning (RBL) model and using the STEM (Science, Technology, Engineering, and Mathematics) approach to improve students' forecasting skills in solving resolving efficient dominating set (REDS) problems. The development of the RBL-STEM device was carried out using the 4D development model (define, design, develop, and disseminate). The developed learning tools meet valid criteria with a percentage of 92.3%, practical criteria with a percentage of 96.26%, and effective with a percentage of 89%. Based on the results of the normality test, it can be concluded that the pre-test and post-test scores are normally distributed because the p-value is higher than 0.05, namely 0.404 and 0.117. Furthermore, the paired samples T-test test produces a p-value that is less than 0.05, namely 0.000, indicating that the pretest and posttest results show that students' forecasting skills have increased statistically significant. Thus, it can be concluded that there is a significant increase in students' forecasting skills after participating in RBL-STEM learning.