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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 22 Documents
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Morphometric Analysis and Stress Orientation of Kaba, Daun, and HulupalikVolcanoes, Bengkulu Province, Indonesia Abimayu, Dadin Mars Abimayu; Hadi, Arif Ismul Hadi; Refrizon; Nanang Sugianto; Sapari Dwiyono; Andre Rahmat Al Ansory; Raihana, Hana Raihana; Hakim, Arieffin Yusuf Hakim; Asy Syifa Auliya Putri Ramadhani
Jurnal Fisika Vol. 14 No. 2 (2024): Jurnal Fisika 14 (2) 2024
Publisher : Universitas Negeri Semarang

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Abstract

Bengkulu Province is an area in Sumatra that is surrounded by Bukit Barisan. This research aims to provide information about the horizontal stress orientation data σHmaxs on the volcanoes of Kaba, Bukit Daun, and Hulupalik, as well as added information about the slope data in the research location that underlies the volcanic arc on the Sumatra Fault. We conducted this research by mapping the morphology of the mountain and determining the straight line of stress orientation, this research uses DEMNAS data of Geospatial Information Agency (BIG). At Kaba Mountain, the maximum stress azimuth angle (σHmaxs) is orientated towards 62° to the East-Northeast/ENE. The direction of plate movement that gives horizontal stress on Kaba volcano is from the east-northeast / ENE and west-southwest / WSW. On Mount Hulupalik determining the azimuth angle of the orientation of the Horizontal stress σHmaxs, the azimuth is towards NNE29°. On Mount Daun where the azimuth angle itself is NNE26°. From the azimuth direction of the horizontal stress (σHmaxs) of Mount Daun and Hulupalik, the plate stress moves from South Southwest/SSW and North Northeast/NNE. Regardless of the direction of horizontal stress/σHmaxs of each mountain, it is influenced by several factors that can cause different stress directions.
Mapping of Natural Frequency, Amplification, Seismic Vulnerability, and Vs30 Velocity in Selebar District, Bengkulu City Siagian, Samuel; Refrizon; Hadi, Arif Ismul
Jurnal Fisika Vol. 15 No. 1 (2025): Jurnal Fisika 15 (1) 2025
Publisher : Universitas Negeri Semarang

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Abstract

Research using the microtremor method has been conducted in Selebar District, Bengkulu City, to estimate the ground response to earthquake vibrations. The purpose of this research is to support building mitigation in earthquake-prone areas. Microzonation mapping is conducted by analyzing the dominant frequency (f0), amplification factor (A0), seismic vulnerability (Kg), and shear wave velocity (Vs30). The Horizontal to Vertical Spectral Ratio (HVSR) method is used in microtremor analysis. The results show the dominant frequencies consist of 40.8% hard gravelly sandstone, 26.5% alluvial rock with a thickness of 5 meters, 18.4% alluvial rock with bluff formation and 14.3% delta sediments. The amplification values include 40.8% in the low category, 56.1% in the medium category and 3.1% in the high category. The seismic vulnerability index indicates that 63.3% is below 3 level, 26.5% is between 3-6 level and 10.2% is between 6-9 level. The shear wave velocity (Vs30) values show that 8.2% is above 1500 m/s, 10.2% is between 750 m/s and 1500 m/s, 55.1% is between 350 m/s and 750 m/s, 25.5% is between 175 m/s and 350 m/s, and 1.1% is below 175 m/s. In conclusion, Selebar District has hard rock layers and low seismic vulnerability, rendering it generally safe from earthquakes.
Synthesis and Characterization of Wall Paint Based on Red Beetroot Betacyanin Pigment with Maceration Randa, Dendy; Nurbaiti, Upik; Fianti; Astuti, Budi; Yulianto, Agus
Jurnal Fisika Vol. 15 No. 1 (2025): Jurnal Fisika 15 (1) 2025
Publisher : Universitas Negeri Semarang

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Abstract

Every year, the paint industry in Indonesia continues to grow. This is due to the growth of the property and housing sectors, which increases the demand for paint nationwide. This research aims to develop environmentally friendly wall paint using betacyanin pigment from red beet tubers through a maceration process as an alternative paint color that is sustainable and beneficial for health and the environment. Betacyanin pigment extraction was carried out using the maceration method with 96% ethanol for 48 hours, then filtered using filter paper and evaporated. Binder and pigment are mixed in a ratio of 14.3:2, 14.3:5, 14.3:8, 14.3:11, 14.3:14, and 14.3:17 until homogeneous. Paint characterization is done through pH, color, density, and adhesion tests. The research results show that the sixth paint variation, with a binder and pigment composition ratio of 14.3 ml:17 ml, provides the most optimal results that closely align with SNI. The paint has a deep red color, pH 7.6, density of 1.18 g/cm³, and adhesion of 100%.
Eyeliner Fabrication from Coconut Shell Waste (Cocos Nucifera) with Xanthan Gum Binder (C35H49O29) Senda, Tamara Rizky; Nurbaiti, Upik; Fianti; Astuti, Budi; Yulianto, Agus
Jurnal Fisika Vol. 15 No. 1 (2025): Jurnal Fisika 15 (1) 2025
Publisher : Universitas Negeri Semarang

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Abstract

Eyeliner is a decorative cosmetic or make-up product. Eyeliner functions to help emphasize and make the shape of the eyes more prominent and more expressive, make makeup more dramatic without doing many steps, and cover the false eyelash line that sticks to the eyes. This study aims to determine whether activated carbon from coconut shell waste can be used as a natural dye in eyeliner fabrication. This research uses a laboratory experiment method, namely by mixing materials consisting of distilled water, xanthan gum, tween 80, propylene glycol, methylparaben, CH_3 COOH solution with distilled water, ethanol, and carbon pigments in it. Xanthan gum and carbon are mixed in a ratio of 1:10; 1:12; 1:14; 1:16; 1:8; and 1:20 until homogeneous.  Fabrication properties were tested, namely homogeneity, pH, drying time, and color tests on eyeliner fabrication. the results were analyzed descriptively. Based on the results obtained, the six fabricated formulations have a deep black color and have an average particle size of 8.1 µm, have an average pH of 6.3, an average drying time of 303 seconds, the six formulations have an evil Minister color, After Dark, Deep Forest chocolate, Holy Crow, Smoked black coffee, Indigo brown ink. It was concluded that pigments from coconut shell carbon can be used as natural dyes in eyeliner fabrication. However, in the physical properties test, namely the homogeneity test and dry time test for eyeliner fabrication, there are still discrepancies in the literature.
2D Numerical Modeling for Estimation of Run Up and Arrival Time of Tsunami at the Coast of Banyuwangi District Alif Aulia Baroroh; Supriyadi; Sutikno; Mochamad Aryono Adhi; Hamzah Latief
Jurnal Fisika Vol. 15 No. 1 (2025): Jurnal Fisika 15 (1) 2025
Publisher : Universitas Negeri Semarang

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Abstract

The Banyuwangi tsunami was generated by an earthquake of magnitude 7.8 that struck the south coast of East Java with Mw 7.8 on June 3, 1994. The tsunami claimed the lives of more than 200 people, and severely damaged infrastructure, buildings and transportation facilities. Many studies have been conducted on the Banyuwangi tsunami, but not many have reviewed the validation of the maximum height compared to the results of field studies in the same year as the June 3, 1994 Banyuwangi tsunami. The study of Banyuwangi tsunami reconstruction aims to validate the maximum tsunami height of the model output compared to the results of field measurements by Tsuji in 1995. This study uses COMCOT v1.7 software with the nested model method. The results of the simulation of tsunami wave propagation that occurred every time period after the earthquake, showed that in snapshot layer 1 and layer 4 within 10 minutes the distribution of the earthquake expanded the tsunami wave propagation, within 30 minutes the tsunami wave propagation had entered several areas of the southern coast of East Java, within 35 minutes the tsunami wave propagation had reached land. The comparison ratio between model results and field measurements is K of 0.811998002 and
PID Based Artificial Neural Network For Rotary Dryer In The Fertilizer Industry Vio Gustian Nur Alamsyah; Celfien Septian Widya Pratama; Dicko Alryadi Samudra
Jurnal Fisika Vol. 15 No. 1 (2025): Jurnal Fisika 15 (1) 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v15i1.20968

Abstract

Rotary dryers are often used to dry materials in fertilizer industry. The drying process using a rotary dryer may occasionally encounter issues, such as an uneven distribution of hot air and overheating, which can be caused by operator input errors or control parameter adjustments that are not optimal. The conventional proportional-integral-derivative (PID) controller is a common method for regulating temperature in rotary dryers. However, it is not particularly effective in dealing with changes that occur in real time, which can result in extending the system’s transient period before equilibrium and overshoot for temperature output in rotary dryers. One potential solution that can be offered is to integrate PID control with an Artificial Neural Network (ANN) which would enable the system to adapt to the dynamics of the operational environment without operator assistance. The methodology used is backpropagation neural networks, trained with empirical data gathered during the operation of a rotary dryer. The output from the ANN model is then used to adjust the PID controller within the system in order to prevent extending the system’s transient period before equilibrium and overshoot. Backpropagation is used because this algorithm can effectively reduce errors when recognizing data patterns. The control design aims to improve the efficiency of the drying process, optimizing it, and reducing costs associated with production
Decomposition Model and Extension of Spring Pendulum Systems in the 21st Century: A Systematic Literature Review Saputra, Rangga Apriliyanto; Saefan, Joko; Siswanto, Joko
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.v15i2.21764

Abstract

A spring pendulum is a mechanical system that describes the reciprocating motion of a mass suspended on a spring around an equilibrium point. The system consists of a spring with certain elasticity characteristics and a fulcrum to which the spring is attached. When the mass is pulled from its equilibrium position, the spring generates a restoring force proportional to the distance of displacement, inducing the mass to move periodically. Spring pendulum systems have seen frequent development in the design of mechanical systems that require high-precision vibration control. This study examines developments in system expansion and equation decomposition models of spring pendulums by conducting a Systematic Literature Review (SLR) of 36 pertinent articles from Scopus and Google Scholar (2000–2024). The main focus of the research lies on the expansion of the basic spring pendulum system through various modifications, which is the dominant topic in the review. The most popular technique for resolving the system's equations of motion is breaking down the equations using analytical mathematical formulations, particularly the Lagrangian method, which refers to the theoretical derivation of equations of motion through well-known mathematical frameworks like Lagrangian and Hamiltonian mechanics. The findings provide deep insights for the development of mathematical models as well as a comprehensive overview of the development of spring pendulum research. The implications of this research can contribute to innovations in engineering, physics, and other related disciplines.
The Future Direction of Radiology: The Role of Artificial Intelligence and Augmented Reality in Medical Visualization Putra, Damianus Dinata; Nisa, Dila Fadilatu; Affan Alfarabi; Dirgayussa, I Gde Eka; Filano, Raffli
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.v15i2.23310

Abstract

The rapid advancement of digital technologies has significantly influenced the field of medical imaging, particularly through the integration of Artificial Intelligence (AI) and Augmented Reality (AR). These technologies offer transformative potential in improving diagnostic accuracy, enhancing surgical planning, and addressing the limitations of traditional radiological methods. This study aims to evaluate the roles and effectiveness of AI and AR in radiology by analyzing their applications in medical diagnosis and surgical visualization, with a focus on increasing diagnostic speed, precision, and accessibility, especially in resource-limited settings. A systematic literature review was conducted by examining 45 peer-reviewed articles published between 2017 and 2025, selected based on relevance, innovation, and applicability. Thematic analysis revealed that AI—especially models using convolutional neural networks—has demonstrated high accuracy in detecting lung disease, breast cancer, and brain tumors. Meanwhile, AR has shown potential in enhancing spatial understanding and accuracy in surgical procedures. Despite these benefits, several challenges were identified, including integration difficulties with existing hospital systems, algorithmic bias, regulatory constraints, and high costs. In conclusion, the integration of AI and AR represents a promising direction for the future of radiology. However, further research is needed to develop cost-effective systems, ensure ethical and inclusive AI training, and establish standardized protocols for implementation. This study provides a foundational overview for healthcare stakeholders aiming to adopt these technologies in pursuit of more equitable and efficient medical imaging practices.
Identification of Brain Areas Associated with Chronic Neuropathic Pain through Hjorth Parameter Analysis of EEG Signals Asyrafi, Hilman; Handayani, Nita; Ilmawan, Lutfi Budi; Shabir, Fadly; Jamal, Ridwan; Jannah, Miftahul; Arysespajayadi
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.v15i2.24512

Abstract

This study investigates the neurophysiological signatures of chronic neuropathic pain (CNP) through the analysis of EEG signals using Hjorth parameters (Activity, Mobility, and Complexity). We compared EEG recordings from 36 CNP patients with those from 19 healthy controls (HC) under both eyes-open and eyes-closed conditions. Analysis of 19 electrode locations revealed significant differences between the groups across all Hjorth parameters. The Activity parameter showed dramatic elevations in CNP patients across all brain regions, indicating widespread cortical hyperexcitability. Mobility parameters revealed significant alterations particularly in occipital (O2), central midline (Cz), and parietal (Pz) regions, with strong effect sizes (Cliff's delta > 0.7). Complexity parameters demonstrated significant changes in right temporal (T4) and parietal midline (Pz) areas. The combined analysis identified the parietal cortex, temporal regions, occipital cortex, and central midline as key areas associated with CNP, suggesting a distributed network disruption rather than localized dysfunction. These findings contribute to our understanding of the neural mechanisms underlying chronic neuropathic pain and may support the development of objective diagnostic markers and targeted interventions for this debilitating condition.
Advancements and Challenges of Deep Learning in Diagnostic Radiology: A Systematic Literature Review Affan Alfarabi; Filano, Rafli; Dirgayussa, I Gde Eka; Akbar, Ridho Lailatul; Zakiah, Hafizah
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.v15i2.27967

Abstract

The rapid integration of Deep Learning (DL) in medical imaging is revolutionizing radiology and addressing critical challenges in diagnostic accuracy and healthcare delivery. In Indonesia and other developing countries, the shortage of radiologists and uneven distribution of healthcare services underline the urgency of exploring DL applications as potential solutions. This study aims to systematically review recent trends, effectiveness, and challenges of DL in diagnostic radiology, as well as to provide insights into its potential adaptation in the Indonesian healthcare system. Using a systematic literature review of peer-reviewed articles (2020–2025) from PubMed, IEEE Xplore, ScienceDirect, and Google Scholar, we identified and synthesized evidence on DL applications across multiple imaging modalities, including CT, MRI, X-ray, and ultrasound. Results show that DL achieves radiologist-level accuracy in tasks such as disease detection, segmentation, and automated report generation, while also improving workflow efficiency and clinical decision-making. However, challenges remain in terms of data availability, model interpretability, ethical issues, and clinical integration. This study provides recommendations for advancing DL adoption in radiology, emphasizing the need for standardized validation, clinician training, and context-specific implementation strategies in Indonesia. The findings highlight both the global and local significance of DL in enhancing healthcare access and equity.

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