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Lontar Physics Today
Published by Universitas PGRI Semarang
ISSN : -     EISSN : 28280970     DOI : https://doi.org/10.26877/lpt
Core Subject : Science, Education,
Education Physics
LONTAR PHYSICS TODAY is a scientific journal published by the Physics Education Study Program, Universitas PGRI Semarang with the scope of all areas in the fields of physics and physics education. Lontar Physics Today papers will be published three times a year on February, June, and Nopember by Physics Education study program, Universitas PGRI Semarang, Semarang, Central Java, Indonesia. Please read this guide carefully. Authors who wish to submit their manuscripts to the editors of the Lontar Physics Today must comply with the writing guidelines. If the submitted manuscript does not comply with the guidelines or is written in a different format, it will be rejected by the editor before further review. The editor will only accept manuscripts that meet the specified format.
Arjuna Subject : Fisika dan Astronomi - Fisika dan Astronomi (Lain-Lain)
Articles 9 Documents
 1 
Search results for , issue "Vol 4, No 3 (2025): November 2025" : 9 Documents clear
Resistivity of SnO2 Gas Sensor to Humidity, CO2 Gas, and Temperature in Food Decomposition Process Setiawan, Indra Budi; Toifur, Moh.; Ishafit, Ishafit; Okimustava, Okimustava; Hajatulloh, Ridlo; Susanto, Eko
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.24866

Abstract

This study aims to determine the sensitivity of a gas sensor based on a Cu substrate coated with SnO2 through an electroplating process, involving variations in electrolyte solution temperature and thermal oxidation. The deposition parameters were set as follows: electrolyte solution prepared by dissolving SnCl2 in distilled water, applied voltage of 4.5 V, electrode distance of 3 cm, and electroplating duration of 3 minutes. Sensor sensitivity tests were carried out by observing the food decomposition process, placing both the food sample and sensor in a testing chamber. Data acquisition of temperature, humidity, CO2 concentration, and sensor resistance was conducted using transducers and Logger Pro software. Based on the results, the sensor sample with an electrolyte temperature of 60°C (sample B) exhibited better performance than the sensor sample with an electrolyte temperature of 30°C (sample A). Sample B demonstrated greater responsiveness to temperature changes, with a coefficient of determination R2 = 0.66943. It also showed better detection of CO2 concentration changes with R2 = 0.98225. This improvement is attributed to a more effective electroplating process, as indicated by the mass change and thickness of the SnO2 layer. The sensitivity of sample B, defined by the equation S([CO2]) = 9.42E-5 - 1.17E-9[CO2], was superior to that of sample A, which followed the equation S([CO2]) = -2.34E-4 + 4.25E-9[CO2], as shown in the plotted graphs. Sample B exhibited a negative linear curve with a gentle slope, indicating a stable gas sensor behaviour.
Analytical Solution of Transverse Electric and Transverse Magnetic Mode Electromagnetic Wave Equations in Left-Handed Materials Handayani, Iryan Dwi; Muliandhi, Puri; Wahjoerini, Wahjoerini; Pamurti, Andarina Aji
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.25060

Abstract

Artificial composite materials that focus on electromagnetic waves are known as metamaterials. Metamaterials are artificial materials engineered by human technology, possessing a geometric structure built from microscopic, engineerable materials. The goal is for the new material to be able to direct light, sound, and waves, making it useful. Metamaterials are known as left-handed materials (LHMs), but the concept of metamaterials is broader than LHM. The purpose of this research is to solve the transverse electric (TE) and transverse magnetic (TM) electromagnetic wave equations in left-handed materials (LHMs) using the Nikiforov-Uvarov approach and to analyze the results of the energy spectrum equation from the solution of the transverse electric (TE) and transverse magnetic (TM) electromagnetic wave equations in left-handed medium (LHM). This research was conducted using Matlab software. The material being studied is the positive-negative gradient profile in an LHM medium thru variations in dielectric permittivity and/or magnetic permeability. Energy and wave equations were obtained with their visualization.
Citizen Science in Science-Physics Class: Building Contextual Climate Change Literacy Andini, Elvina Risma; Siswanto, Joko
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.25078

Abstract

This study aims to examine the potential of integrating Citizen Science (CS) into science-physics learning as a pedagogical approach that can help shape a contextual understanding of climate change. This study used the Systematic Literature Review (SLR) method with reference to the PRISMA 2020 guidelines. The review process was carried out through several steps, namely problem identification, literature search in various databases, determination of inclusion and exclusion criteria, selection of articles, and thematic analysis of literature that met the criteria. Of the 35 articles identified, 15 were selected for further in-depth analysis. The literature review indicates that the integration of CS into science-physics learning can effectively improve cognitive aspects (scientific literacy, critical thinking skills, and creativity), affective (positive attitudes towards the environment, self-confidence, and relationships with the scientific community), and behavioral (awareness of pro-environmental actions). However, significant behavioral changes are still limited, and implementation faces obstacles such as limited time, lack of teacher competence, and integration with the official curriculum. The uniqueness of this study lies in mapping the contribution of Citizen Science in strengthening students' climate literacy comprehensively. Citizen Science serves not only as a science learning method but also as a medium of scientific and social participation that connects scientific knowledge, environmental awareness, and concrete action.
Content Analysis of Socio-Scientific Issues Research in Physics Learning 2020-2025: Systematic Literature Review Indraswari, Anisa Wulan; Wahyuni, Siti
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.24894

Abstract

This study aims to identify trends and directions of studies related to the socio-scientific issues (SSI) approach in physics education. Using the Systematic Literature Review (SLR) method, 11 articles published between 2020-2025 were analyzed through a bibliometric approach and content analysis. The results show that the SSI approach is not only utilized as a learning strategy, but also as a transformative tool that integrates cognitive, affective, and social values aspects. Energy topics and environmental issues dominate the learning context, while other physics topics such as waves and modern physics are less explored. In addition, there is a tendency to apply SSI at the high school level, which is considered more cognitively prepared and reflective. This research recommends diversifying the context of SSI and strengthening teachers' capacity in designing contextual and meaningful physics learning in the post-pandemic era.
Intensity of Artificial Intelligence (AI) Use for Physics Learning in High Schools Rende, Jeane Cornelda; Lahope, Kenny Setiawan
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study investigates the intensity of Artificial Intelligence utilization in Physics education at a public high school in Manado City, Indonesia. The research aimed to understand the patterns and extent of AI integration, as well as the influencing factors, through a qualitative case study approach. The methodology involved in-depth interviews, classroom observations, and document analysis with six Physics teachers, students, and school management selected via purposive sampling. Data were analyzed using Miles and Huberman's model and thematic analysis. Key parameters examined included the forms of AI usage, intensity levels (low, medium, high), frequency, depth of utilization, and both supporting (teacher digital competence, school policy support, student enthusiasm) and hindering factors (lack of formal pedagogical training, infrastructure limitations, cultural resistance). Important findings indicate that AI adoption is predominantly at a medium level, primarily utilizing interactive simulations like PhET Interactive Simulation for abstract concept visualization, which significantly enhances student engagement and comprehension. However, comprehensive AI integration for adaptive, personalized learning remains rare. While school facilities are generally supportive, teachers' digital readiness varies, and AI usage frequency averages one to two times per week, the depth of its application often remains instrumental rather than transformational. In conclusion, AI adoption in Physics learning is still nascent, not yet fully optimizing AI's potential as an adaptive intelligent learning system, largely due to variations in teacher competency, school policies, and infrastructure readiness.
Digital Experiments in Learning the Concept of Gravitational Force in Classical Mechanics Mahombar, Alexander
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.25245

Abstract

Gravitational force is one of the fundamental forces that plays an important role in understanding the interaction between massive objects in the universe. However, in physics education, this concept is often difficult to understand concretely due to the limitations of real experiments. This research purpose to analyse the relationship between mass, distance, and gravitational force using the PhET Gravity Force Lab: Basics interactive simulation, as well as to prove its conformity with Newton's Law of Gravity. The research method used was a virtual experiment with a quantitative descriptive approach. Data was obtained by conducting three stages of experiments, namely observing gravitational force on objects of the same and different masses, the relationship between force and mass at a fixed distance, and the relationship between force and distance at a fixed mass. The results showed that gravitational force increased as the mass of objects increased and decreased significantly when the distance between objects increased. The conclusion of this study was that it proved the theory that gravitational force is directly proportional to the product of the masses of the two objects and inversely proportional to the square of the distance between them, in accordance with Newton's Law of Gravity, and showed that the forces were opposite but equal in magnitude, as described in Newton's Third Law.
Arduino Uno Based Automatic Fruit Maturity Detection System for Orange (Citrus sp.) and Bell Fruits (Syzygium aqueum) Using Electrical Conductivity Ummah, Auliya Rahmatul; Fitriani, Ade; Nur Hanafi, Kholis; Syahrir, Syahrir; Supriyanto, Supriyanto; Zarkasi, Ahmad
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.25513

Abstract

Accurate determination of fruit ripeness is essential to maintain product quality, flavor, and market value. However, traditional manual assessment methods, which rely on sensory observation (color, aroma, and texture), are often subjective and inconsistent. This study aims to design and develop an automatic fruit ripeness detection system based on electrical conductivity measurement in oranges and bell fruits. The system utilizes a three-electrode stainless steel needle probe connected to an ADS1115 Analog-to-Digital Converter (ADC) module and an Arduino Uno microcontroller. A refractometer was used for system calibration and reference data acquisition. Measurements were performed by inserting the probe into the fruit pulp to read the voltage value of the fruit's fluid. This electrical signal was correlated with the reference sugar content (%Brix) and subsequently classified into three categories: ripe, half-ripe, and unripe. Results show that the average voltage range for oranges in the ripe, half-ripe, and unripe categories was 2.74 V, 2.58 V, and 2.32 V, respectively. For bell fruits, the corresponding voltage ranges were 2.48 V, 2.26 V, and 2.08 V. These voltage values were derived from the experimental data presented in Table 1 and  Table 2. The abstract  reports the average voltage for each ripeness category, whereas the tables list individual measurement values, resulting in slight differences between the summarized and detailed data. The average relative error of the measurement was found to be approximately 5 %, which is considered acceptable for practical field application. This indicates that the developed system is capable of classifying fruit ripeness in a non-destructive, accurate, and rapid manner.
Effects of Integrating Deep Learning with a Project-Based Learning Model on Thermodynamics Learning Outcomes Makahinda, Tineke; Lahope, Kenny Setiawan; Kuron, Meidy Atina
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.25521

Abstract

This study investigates the difference in Thermodynamics learning outcomes between students taught using a Project-Based Learning (PBL) model integrated with deep learning and those taught using the PBL model alone.. The research employed an experimental method with a quasi-experimental design, utilizing a Nonequivalent Pretest-Posttest Control Group Design. The study was conducted in the Physics Department of Manado State University for Physics Education and Physics programs during the Odd Semester of the 2025/2026 Academic Year. The research population included all active students from these programs, with a random sample of 40 students divided into an experimental class and a control class, each consisting of 20 students. Data were collected through essay-type tests, administered as pretests and posttests, and subsequently analyzed statistically using descriptive and inferential techniques with Python programming. The findings indicate that the experimental class, which implemented deep learning integrated with the Project Based Learning model, achieved a higher average Thermodynamics learning outcome (80.28) compared to the control class (72.35), demonstrating better data consistency (standard deviation of 7.93 versus 9.71). Shapiro-Wilk normality tests for both classes confirmed a normal distribution of data (p-value for experimental class is 0.3147 while control class is 0.0638), and Levene's homogeneity test confirmed homogeneous variances (p-value 0.2529). Furthermore, the independent sample t-test results showed a t-statistic of 2.8289 and a p-value of 0.0074, which is less than 0.05. This leads to the conclusion that there is a statistically significant difference in Thermodynamics learning outcomes between the experimental and control classes. These findings suggest that the integration of deep learning with the Project Based Learning model is effective in enhancing Thermodynamics learning outcomes.
The Effectiveness of the Application of the Virtual Lab-Assisted ARIAS Learning Model on Motion and Force Materials in Improving the Cognitive Learning Outcomes of Grade VII Students of SMPN 1 Bangko Pusako Ferdiansyah, Ferdiansyah; Irianti, Mitri; Ernidawati, Ernidawati
Lontar Physics Today Vol 4, No 3 (2025): November 2025
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/lpt.v4i3.25653

Abstract

The low achievement of student learning outcomes is due to the lack of interest and activity of students in the learning process. Students do not understand the material and are not active during learning due to the monotonous learning model. This study is to describe and determine the effectiveness of the application of the ARIAS learning model combined with a virtual lab on motion and force materials in improving the cognitive learning outcomes of grade VII students of SMPN 1 Bangko Pusako. The study used a quasi-experiment approach with a Non-Equivalent Post-test Only Group Design. The sample consisted of two classes, namely the control class (28 students) and the experimental class (29 students). The research instrument is in the form of an objective test to determine students' cognitive learning outcomes. The data were analyzed through normality, homogeneity, and hypothesis tests. The results of the study stated that there was a significant difference in the cognitive learning outcomes of students in both classes. The average score of the experimental class was 71.7 (good category), and the control class got an average score of 53 (good category). After the Mann-Whitney U Test, a significance value of 0.000 (0.05) was obtained, so it was concluded that the virtual lab-assisted ARIAS model was effective in improving students' cognitive learning outcomes on motion and force materials.

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