Indonesian Review of Physics

Non-Invasive Blood Glucose Estimation Using PPG Derivative Features and MFCCs with Random Forest

2026-05-01T07:15:50+00:00

Conventional blood glucose measurement devices remain dominated by invasive methods that require direct contact with body tissues and cause patient discomfort, motivating the development of accurate and non-invasive blood glucose monitoring approaches. Therefore, blood glucose estimation has performed using Photoplethysmography (PPG) signals by exploiting the Velocity Photoplethysmogram (VPG) and the Acceleration Photoplethysmogram (APG) as derivative signals. PPG signals were acquired non-invasively from 58 participants using an optical MAX30102 sensor placed on the finger. Morphological fiducial features and Mel-Frequency Cepstral Coefficients (MFCCs) were extracted from PPG, VPG, and APG signals to capture temporal, morphological, and spectral characteristics related to peripheral hemodynamic changes. The extracted features were then used to model blood glucose levels using a Random Forest algorithm. The results showed that the combined use of PPG, VPG, and APG produced the best performance, achieving Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Relative Difference (MARD) values of 6.35 mg/dL, 9.74 mg/dL, and 6.07%, respectively. Clarke Error Grid Analysis (CEGA) showed that 97.44% of the predictions were located in Zone A and 2.56% in Zone B, indicating that all estimates were within clinically acceptable regions. The main scientific contribution of this study lies in integrating derivative PPG signals with fiducial and MFCC-based feature representations within a unified machine learning framework. These findings indicate that combining PPG, VPG, and APG provides a richer physiological representation than PPG alone and offers practical potential for the development of wearable-based, non-invasive blood glucose monitoring technology.

The Integration of Hybrid and Game-Based Learning in Physics Education: A Systematic Review of Their Effects on Critical Thinking and Problem-Solving Skills (2018 - 2024)

2026-03-17T01:41:00+00:00

This study aims to analyze the impact of integrating hybrid and game-based learning on critical thinking and problem-solving skills in physics education and to identify research trends from 2018 to 2024. The method used was a systematic literature review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The literature search was conducted through Scopus, Web of Science, and Accredited National Journals databases using a combination of relevant keywords. Inclusion criteria included empirical research articles published in English or Indonesian between 2018 and 2024. The selection process involved the stages of identification, screening, eligibility assessment, and inclusion. A total of 16 articles were analyzed further. Data were analyzed using thematic synthesis techniques to identify patterns, methodological trends, and key findings from the reviewed studies. The results indicate that hybrid learning has a more consistent impact on enhancing critical thinking and problem-solving skills, particularly through problem-based approaches and technological support. Meanwhile, game-based learning contributes more to improving motivation, engagement, and understanding of physics concepts. This study contributes a thematic synthesis and comparative analysis of the integration of hybrid and game-based learning and serves as a conceptual foundation for the development of technology-based physics learning models to enhance critical thinking and problem-solving.

Comparative Simulation Study of Impedance Enhancement in a Circular UWB Antenna Using Defected Ground Structure and Slot Techniques

2026-05-01T13:00:28+00:00

This study presents a comparative simulation analysis of impedance enhancement in a circular UWB microstrip antenna using Defected Ground Structure (DGS) and slot techniques. Three antenna configurations were investigated: a baseline circular antenna, a DGS-loaded antenna, and a combined DGS-slot antenna. All antenna models were designed and simulated using CST Studio Suite with identical simulation conditions to evaluate the progressive effect of each structural modification. The antenna performance was analyzed in terms of S11, VSWR, input impedance, realized gain, radiation efficiency, and radiation pattern. The results show that the combined DGS-slot antenna provides the best impedance-matching performance, achieving S11 below -10 dB from approximately 1.72 GHz to 13.06 GHz, corresponding to a continuous bandwidth of 11.34 GHz. This represents a bandwidth improvement of approximately 223.6% compared with the baseline antenna and 69.3% compared with the DGS-loaded antenna. The optimized antenna also achieves a minimum VSWR of approximately 1.01 at 7.66 GHz and an input impedance of 50.46 + j0.35 Ω near resonance. In addition, the antenna provides a realized gain of 4.735 dBi and radiation efficiency of 79.27% at 7.6 GHz. These results demonstrate the synergistic effect of DGS-slot coupling in improving impedance matching, bandwidth continuity, and radiation performance of circular UWB antennas

Critical Analysis of High School Students' Metacognitive Awareness of Physics Using Rasch Modeling

2026-03-17T08:45:53+00:00

Development of the 5E-POW (Predict–Observe–Write) Learning Model Assisted by Virtual Simulation to Reduce High School Students' Misconceptions on the Topic of Fluids

2026-05-01T03:19:08+00:00

This study aims to develop 5E-POW (Predict–Observe–Write) learning model supported by virtual simulation to reduce high school students’ misconceptions about fluid topics. The research employed the ADDIE development model consisting of Analysis, Design, Development, Implementation, and Evaluation stages. The participants were 25 third-semester students from the 2024 PFA cohort selected through simple random sampling. Data were collected using a four-tier diagnostic test consisting of 29 items to identify students’ misconceptions before and after implementation. The collected data were analyzed using validity analysis, misconception reduction analysis, N-gain analysis, normality testing, and a paired-samples t-test. The results showed that the developed learning model and learning instruments were categorized as very valid, while the virtual simulation media were categorized as valid, requiring minor revisions. Furthermore, the implementation of the 5E-POW learning model assisted by virtual simulation effectively reduced students' misconceptions on several fluid concepts, including hydrostatic pressure (49.71%), Pascal's law (35.20%), Archimedes' principle (49.34%), discharge and continuity (47.00%), and Bernoulli's principle (55.00%). Statistical analysis also indicated that the data were normally distributed and that there were significant differences between the pretest and posttest results. The novelty of this research lies in integrating the 5E Learning Cycle, the Predict–Observe–Write strategy, and virtual simulation into a single instructional framework specifically designed to facilitate conceptual change and reduce misconceptions in physics learning.