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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA)
Irwandi
Syiah Kuala University
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics

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Implementing R-STEM and the ISLE Model to Enhance Students' Conceptual Understanding of Magnetic Induction at Unsyiah Laboratory School Yulma Erma Yanti; Irwandi; Rini Safitri; Nizammuddin; Razief Perucha Fauzie Afidh; Muzakiah; Hasrati; Nurul Azmi; Ahmad Anwar Zainuddin; Amir ‘Aatieff Amir Hussain; Mohd Khairul Azmi Hassan
Jurnal Penelitian Pendidikan IPA Vol 11 No 3 (2025): March
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i3.8665

Abstract

Many schools face difficulties in implementing science education through a practicum due to insufficient laboratory facilities and bureaucratic constraints, which hinder students' hands-on learning. To address such constraints, a new web-based remote laboratory, Remote STEM (R-STEM) platform, was introduced by the STEM Research Center. This study explores using R-STEM in learning magnetic induction using the ISLE-based STEM approach with Student Activity Sheets (LKPD) to enhance engagement. A mixed-methods research design was utilized, and 72 high school students underwent a set of experiments according to the ISLE cycle, from observations to pattern detection, explanation, predictions, and experimentation verification. The results show a high rate of students’ understanding of magnetic induction, with a score in LKPD evaluation at 84%, a rate of implementation at 93%, and a score in learning activity alignment at 78.5%. In addition, pretest and posttest tests showed a learning outcome increase by 71%. This study contributes to the broader scientific educational community by demonstrating that remote laboratories can be effective in enhancing STEM learning, particularly in schools with fewer laboratory facilities.
Application of a Levenberg–Marquardt-Based Backpropagation Neural Network for Rainfall Prediction Using a Single Weather Station Wahyu Sukmananda; Irwandi; Edwar Iswardy; Kadarsah; Yopi Ilhamsyah; Yuwaldi Away; Chakrit Chotamongsak; Dedy Ardana
Jurnal Penelitian Pendidikan IPA Vol 12 No 2 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i2.13845

Abstract

This study aims to develop an accurate monthly rainfall prediction model for Sabang City, Indonesia, to support agriculture, disaster mitigation, and water resource management in coastal regions with complex climatic conditions. An Artificial Neural Network (ANN) trained using the Levenberg–Marquardt (LM) algorithm was employed, combining the Gradient Descent and the Gauss–Newton methods to enhance convergence speed and training stability. Meteorological data from 2015–2024, including temperature, humidity, air pressure, sunshine duration, wind direction, wind speed, and rainfall, were obtained from the Maimun Saleh Meteorological Station. Model performance was assessed using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The optimal architecture consisted of a single hidden layer with 25 neurons, producing an MSE of 955.84 mm², an RMSE of 30.91 mm, an MAE of 23.06 mm, a MAPE of 34.8%, and an R² of 0.93. These results indicate that the ANN-LM model effectively captures nonlinear climatic relationships and seasonal rainfall variability. The MAPE value falls within the acceptable range reported in forecasting literature, demonstrating practical reliability. Overall, the ANN-LM approach outperformed conventional backpropagation in accuracy and training efficiency, indicating its suitability for rainfall prediction in coastal areas.
Co-Authors Ahmad Anwar Zainuddin Amir ‘Aatieff Amir Hussain Chakrit Chotamongsak Dedy Ardana Edwar Iswardy Hasrati Kadarsah Mohd Khairul Azmi Hassan Muzakiah Nizammuddin Nurul Azmi Razief Perucha Fauzie Afidh Rini Safitri Wahyu Sukmananda Yopi Ilhamsyah Yulma Erma Yanti Yuwaldi Away