1 Department of Postgraduate of Mathematics Education, University of Jember, Indonesia.
2 Department of Computer Science, University of Jember, Indonesia.
Research Article
World Journal of Advanced Research and Reviews, 2024, 21(01), 2233-2241
Article DOI: 10.30574/wjarr.2024.21.1.0217
Received on 07 November 2023; revised on 22 January 2024; accepted on 24 January 2024
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.
Forecasting Skills; REDS; RBl-STEM; Multistep Forecasting
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Zulfatu Zainiyah, Arika Indah Kristiana, Slamin and Dafik. The development of RBL-STEM learning materials to improve the students’ forecasting skills in solving resolving efficient dominating set for hydroponic farming. World Journal of Advanced Research and Reviews, 2024, 21(1), 2233-2241. Article DOI: https://doi.org/10.30574/wjarr.2024.21.1.0217