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Jurnal Fisika
Published by Universitas Negeri Semarang
ISSN : -     EISSN : 2684978X     DOI : https://doi.org/10.15294/jf
Core Subject : Science,
Physics
urnal Fisika coverage extends across the whole of physics, encompassing pure, applied, theoretical and experimental research, as well as interdisciplinary topics. Research areas covered by the journal include
Arjuna Subject : Fisika dan Astronomi - Fisika dan Astronomi (Lain-Lain)
Articles 28 Documents
 1   2   3 
Synthesis of Carbon Quantum Dots and Their Optical Properties Under Various Conditions Dhobi, Saddam; Hangsarumba, Surendra; Kamat, Raman Kumar; Yadava, Kishori; Gupta, Suresh Prasad
Jurnal Fisika Vol. 15 No. 2 (2025): Jurnal Fisika 15 (2) 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v15i2.33311

Abstract

Carbon quantum dots (CQDs) are nanomaterials that possess great optical properties, and they hold potential for being used in biosensing, imaging, and optoelectronics. The aim of this work is to synthesis, characterization and study the optical properties of CQDs under various condition. In the present work, CQDs have been prepared by mixing equal amount (citric acid and urea) and heating in microwave at 165 °C-180 oC for 2 min to obtained dark brown color. The dark brown power was characterizations using FTIR to confirmed the different functional groups such as –P–O, –S–O, – O–C, C=C C=N and CH2/CH3 (oxygenated-, nitrogenated- and aromatic-types), while XRD analysis indicated the valuable crystalline organic phases with heterogeneous functionality features. The optical properties were carried out in water and sugar solutions (100–155mg/dl) as function of CQDs concentration, temperature, frequency and UV activation times using a Theremino spectrometer. The fluorescence intensity was enhanced with the increase of citric acid and was quenched by urea. In sugar at higher CQD concentrations, intensity was decreased from molecular trapping and light scattering. The fluorescence intensity exhibited fluctuations in water during 60s with red and blue-shifts, and the maximum peak was at 545 nm. The intensity increased with decreasing CQD: water ratio and decreased at higher concentrations, because of absorption and scattering. The temperature and frequency have strong effects on the optical responses; the higher temperatures (58 °C) promote dispersed aggregates in finer particles which leads to more light transmission in addition to larger absorption values at higher frequencies. This demonstrated the tunable features of CQDs optical properties and might give suggestions for subsequent optimization for their applications in biosensing, imaging, and optoelectronics.
Development of Sound-Absorbing Composites Made from Water Hyacinth Waste and Recycled Cardboard Anastasya, Agitha; Widyaningsih, Ayu; Firmansyah, Lucky Fathoni
Jurnal Fisika Vol. 15 No. 2 (2025): Jurnal Fisika 15 (2) 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v15i2.37524

Abstract

Noise is a factor that can disrupt the comfort and effectiveness of daily activities, including learning. To address this issue, this study develops an environmentally friendly sound-absorbing material made from water hyacinth and cardboard, both of which possess natural porosity suitable for acoustic applications. This experimental research aims to determine the sound absorption coefficient of composite materials produced from various combinations of these wastes. Five composite variations were prepared: Sample A (4 g water hyacinth, 4 g cardboard, 8 g matrix), Sample B (5 g water hyacinth, 3 g cardboard, 8 g matrix), Sample C (3 g water hyacinth, 5 g cardboard, 8 g matrix), Sample D (4 g water hyacinth, 4 g cardboard, 9 g matrix), and Sample E (4 g water hyacinth, 4 g cardboard, 7 g matrix). The absorption coefficient was measured using an impedance tube. The results showed that each composition produced different absorption coefficients. Sample D, with a composite-to-matrix ratio of 7:9, had the highest sound absorption coefficient of 0.327 at a frequency of 100 Hz. Meanwhile, Sample E, with a composite-to-matrix ratio of 9:7, had the lowest coefficient of 0.014 at 350 Hz. The findings indicate that water hyacinth and cardboard can be utilized as sound-absorbing materials, with absorption coefficients ranging from 0.01 to 0.32, thereby meeting the ISO 11654 standard.
Analysis of Rainwater Acidity in Semarang City Sri Wulan Siti Khotijah; Sri Endah Ardhi Ningrum Abdullah; Abdul Latif; Sunarno; Dwi Atmoko
Jurnal Fisika Vol. 16 No. 1 (2026): Jurnal Fisika 16 (1) 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v16i1.7919

Abstract

Rainwater is the result of the evaporation process that condenses and falls to the earth's surface. On its way, rainwater mixes with dust particulates and greenhouse gases such as carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NOx), nitrous oxide (N2O), methane (CH4), and other hydrocarbons. This mixture can produce acid rain if the pH of the rainwater is below 5.6. Analyzing the potential for acid rain in urban areas is important as an early detection measure of potential environmental damage. In Semarang City, which has high traffic density and industrial areas, this study examined the acidity of rainwater during the period 2016-2023. The primary data used were rainwater pH data and chemical compounds from the BMKG Air Quality Testing Laboratory. The data were analyzed descriptively to determine the level of acidity and the content of chemical compounds in rainwater. The results showed that the frequency of acid rain in Semarang peaked in 2020 with 83.3%. Strong acid compounds, such as SO4, NO3, and Cl, dominate the chemical content of rainwater with an average of 62.4%, while strong bases and weak bases are 28.7% and 8.9%, respectively. SO4 and NO3 compounds, which originate from motor vehicle emissions, are the main components determining acid rain in this region. This study provides an important rationale for mitigating and preventing the negative impacts of acid rain in Semarang City
Exploring the Impact of Cd Doping on the Crystal Structure and Electrical Properties of ZnO Using Pymatgen-Based Simulation Aprilia Dewi Ardiyanti; Tanzilal Mustaqim; Allif Rosyidy Hilmi; Yofinda Eka Setiawan; Aslam Chitami Priawan Siregar
Jurnal Fisika Vol. 16 No. 1 (2026): Jurnal Fisika 16 (1) 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v16i1.36257

Abstract

Advances in computing technology are driving the development of advanced materials research. This study aims to model and compare the semiconductor properties of ZnO and ZnO doped with Cd (x=0.5) to form Zn0.5Cd0.5O using a computational approach based on Python Materials Genomics (Pymatgen 3.0) approach within a Python 3.10.18 environment. Modeling was carried out to analyze changes in crystal structure, band gap values, and the correlation between charge carrier concentration and temperature. BSDOS Plotter based on Density Functional Theory (DFT) calculations, was used for energy and Density of States (DOS) graph analysis. The simulation results show that the crystal structure of both materials has a wurtzite lattice shape with angles α = β = 90° and χ = 119°. The band gap value of ZnO is obtained at 3.1 eV, while in Zn0.5Cd0.5O it decreases to 2.7 eV due to the influence of Cd doping which lowers the conduction band energy. The temperature ranges from 500K to 600 K the charge carrier concentration in ZnO increases from 3x10⁵/cm³ to 10⁸/cm³. Meanwhile, the concentrations of electron and hole Zn0.5Cd0.5O increase to 10⁸/cm³ and 7x10⁷/cm.
Effect of Electrolyte Concentration and Nafion Membrane Separators on Discharge Dynamics and Voltage Stability of Supercapacitors Saddam Dhobi; Jagendra Chaudhari; Sangita Rai
Jurnal Fisika Vol. 16 No. 1 (2026): Jurnal Fisika 16 (1) 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v16i1.37163

Abstract

This study investigates the effects of Na₂SO₄ electrolyte concentration and Nafion membrane separators on the self-discharge behavior, discharge dynamics, capacitance, and voltage stability of supercapacitors, aiming to identify optimal conditions for enhanced charge retention and long-term energy storage. Supercapacitors were fabricated with Nafion separators and charged at different voltages (1.0, 1.2, and 1.4 V) for varying durations (1, 1.5, and 2 minutes). Self-discharge was monitored, capacitance was calculated using the capacitor discharge equation, and discharge tests were conducted through a 500-ohm resistor to simulate realistic operating conditions. The results demonstrate that supercapacitors with Nafion separators and 0.5 M Na₂SO₄ electrolyte exhibit significantly lower self-discharge rates and more stable voltage profiles compared with those using napkin paper separators. Additionally, higher charging voltages and longer charging times improve charge retention. These findings indicate that the combination of Nafion membranes and optimized electrolyte concentration effectively enhances supercapacitor performance, providing a practical strategy for reliable and efficient energy storage applications.
Comparison of Ultrasound Image Classification Methods for Benign and Malignant Breast Tumors Based on Texture and Shape Characteristics Nova Senandung; Nanda Firdayana; Dewi Anggun Puspita Septiani; Syahwa Ais Saputri; Heni Sumarti
Jurnal Fisika Vol. 16 No. 1 (2026): Jurnal Fisika 16 (1) 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v16i1.39242

Abstract

Early detection of breast tumors is important to  accurately distinguish benign and malignant lesions  . This study aims to compare the performance of Random Forest and Naïve Bayes algorithms in the classification of breast ultrasound images based on texture and shape features. The dataset comes from BUSI which consists of two classes: benign 891 images and malignant 421 images, with images through the pre-processing stage, histogram feature extraction, GLCM, as well as morphological features (circularity and elongation). Feature rankings using Relief show that GLCM Homogeneity has the greatest contribution in distinguishing the two classes. Performance evaluation was carried out using K-Fold Cross Validation with  variations of K=5, 10, 15, 20, and 25. The results showed that consistently placed Random Forest as the best-performing model. Random Forest achieved the highest accuracy at k-fold-5 at 74.18%, with stable AUC values at 0.771-0.777, sensitivity reaching 78.25%, and better specificity (62-63%) across the fold. In contrast, Naïve Bayes showed lower accuracy with a maximum value of 59% at k-fold-25, AUC in the range of 0.68, and low specificity (42-43%) despite the relatively high sensitivity. These findings confirm that across all k-fold validations, Random Forest remains the most balanced and reliable model for distinguishing benign and malignant in breast.
Comparative Analysis Of MRI Image Classification Methods Based On Texture Features For Brain Tumor Detection Using Random Forest Moch. Husain; Delia Okta Rahmadani; Muhammad Akmal K. H; Heni Sumarti
Jurnal Fisika Vol. 16 No. 1 (2026): Jurnal Fisika 16 (1) 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v16i1.39267

Abstract

Medical personnel struggle to detect brain tumors including glioma and meningioma and pituitary tumors because these tumors display matching MRI features which produces different interpretation results between different observers. The research aims to identify three brain tumor types by analyzing MRI image textures and it assesses different classification methods. The Weka software analyzed 3,900 MRI images through Histogram and Gray Level Co-occurrence Matrix (GLCM) and GLRLMGray Level Run Length Matrix (GLRLM) feature extraction methods before Support Vector Machine (SVM)[SF1.1][A1.2] and Naive Bayes and Multilayer Perceptron and Multiclass Classifier and Random Forest algorithms conducted the classification tasks. The analysis revealed that each tumor pair possesses distinct dominant texture characteristics which consist of standard deviation for glioma–meningioma and energy for glioma–pituitary and homogeneity for meningioma–pituitary. The Random Forest algorithm achieved the best classification results in all experiments because it reached 88.62% accuracy for glioma–meningioma and 96.96% accuracy for glioma–pituitary and 95.92% accuracy for meningioma–pituitary while maintaining high sensitivity and specificity values. The research demonstrates that brain tumor MRI image identification becomes more accurate through the combination of texture features with Random Forest classification methods which leads to better medical diagnostic results.
Meteorological Influences on PM2.5 and PM10 Concentrations during Haze Periods in West Sumatra: A Case Study from May to July 2025 Aditya Prapanca; Muhammad Ansori Hasibuan
Jurnal Fisika Vol. 16 No. 1 (2026): Jurnal Fisika 16 (1) 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v16i1.41289

Abstract

Forest and land fires during May–July 2025 in West Sumatra triggered haze events that significantly degraded air quality through increased concentrations of PM2.5 and PM10. This study aims to characterize the temporal variability of PM2.5 and PM10 and to assess the influence of meteorological parameters on particulate matter dynamics during the haze period. The results show a significant increase in PM2.5 and PM10 concentrations during the fire period, with fine particles dominating, as indicated by PM2.5/PM10 ratios exceeding 0.6. PM2.5 and PM10 exhibit a very strong positive correlation, suggesting common emission sources. Although most meteorological parameters display weak correlations with particulate concentrations, multivariate regression reveals that relative humidity and wind speed—particularly in the upper atmospheric layer—significantly influence PM variability. These findings indicate that meteorological conditions act as modulators of particulate concentrations, while forest fire emissions remain the primary driver of elevated PM levels during haze episodes.

Page 3 of 3 | Total Record : 28

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