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Spektra: Jurnal Fisika dan Aplikasinya

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Published by Universitas Negeri Jakarta

ISSN : 25413384 EISSN : 25413392 DOI : -

Core Subject : Science, Engineering,

Aerospace Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics

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Articles 260 Documents

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Advancing X-Ray Medical Imaging through Compton Scattering Technologies: A Systematic Review of Technological Developments and AI-Based Image Reconstruction Ramadhani, Neysya Ditha; Murnia; Dwicahyani, Rania; Akhsan, Hamdi; Ariska, Melly
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 2 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 2, August 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.102.05

Compton scattering has emerged as a promising advancement in X-ray medical imaging, offering enhanced spatial resolution and diagnostic precision compared to conventional techniques. This study employs a Systematic Literature Review (SLR) to evaluate the contributions of Compton scattering technologies in improving imaging performance. Forty peer-reviewed articles were selected from six major databases including Google Scholar, Scopus, PubMed, Web of Science, ScienceDirect, and arXiv based on predefined inclusion criteria. The review identifies three main technological approaches which are Compton cameras, inverse Compton X-ray sources, and Compton scattering tomography. Recent innovations in image reconstruction, particularly using deep learning and convolutional neural networks, have significantly improved image quality, reduced noise, and enhanced computational efficiency. These findings underscore Compton scattering’s clinical potential, especially in soft tissue visualization and early lesion detection. This paper provides a detailed overview of current progress and strategic pathways in the development of Compton based imaging systems towards their clinical application.

One-Dimensional Modeling of Magnetotelluric Data using Convolutional Neural Network-Gated Recurrent Unit Based Inversion and Its Implementation on Field Data Fikri, Achmad Aulia; Nurhasan; Rahmadini, Marshanda Adisti; Abraar, Auza Naufal; Fauzi, Hamzah Firoos; Fitriani, Dini
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 2 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 2, August 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.102.04

The magnetotelluric method is a geophysical method that utilizes natural variations in the electromagnetic field to map the resistivity distribution beneath the surface. In this method, inversion is the primary process used to estimate the resistivity structure from field data. This study proposes a deep learning-based approach for one-dimensional magnetotelluric inversion, combining Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) as an alternative inversion method. The dataset consists of 20 layers with resistivity and thickness values randomly selected within a specific range at 4000 meters depths and a probability value. Apparent resistivity and phase are obtained through forward modeling based on selected resistivity and thicknesses as input, while the resistivity structure is used as output, with a large data sample. The dataset was standardized and normalized using a logarithmic scale and the MinMax method to map values into the 0-1 range. The dataset was used to train the proposed CNN-GRU model, which is capable of mapping the resistivity distribution in the subsurface. The results show that the CNN-GRU model could map the resistivity distribution model and predict its thicknesses with small error based on the apparent resistivity and phase data, indicating that it can be used for one-dimensional inversion in magnetotellurics. Nevertheless, the model performed quite well on several field datasets, showing a good fit between predicted and true values.

Analysis of the Effect of ZnO, FeO, MnO, and MgO Dopants on the Optical Properties of P2O5-CaO Glass System and Comparison With P2O5-Eggshell Glass System Haifany; Eka Laela Nun Karina; Selsa Sururiyah Sya’baniah; Zahra Sajidah Hariyawan; Haryanto; Agus Setyo Budi; Anggara Budi Susila; Hadi Nasbey
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 2 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 2, August 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.102.06

This study investigates the effect of ZnO, FeO, MnO, and MgO dopants on the optical properties of phosphate-based glass within the P₂O₅–CaO system and compares the results with glasses using eggshell-derived CaO as an alternative calcium source. The glass samples were synthesized using the melt quenching method, followed by characterization using Energy Dispersive X-ray (EDX) and UV-Visible spectroscopy. EDX analysis confirmed that phosphorus and oxygen were the dominant elements in all samples, with successful incorporation of each dopant as a network modifier. UV-Vis analysis revealed that the optical properties of the glass were significantly affected by both dopant type and concentration. The addition of ZnO decreases absorbance and widens the band gap up to 10 mol%, indicating improved structural regularity of the glass network. MnO exhibits a non-linear trend, with the highest absorbance observed at 5 mol% and decreasing at higher concentrations. The band gap varies from 3.37 eV to 3.59 eV, suggesting a transition from a disordered to a more stable and compact glass structure. In contrast, FeO and MgO doping reduced the band gap energy due to increased formation of non-bridging oxygen and network disruption. Additionally, comparison with eggshell-derived CaO showed higher UV absorbance compared to glass made with pure CaO, especially in the wavelength range below 400 nm, indicating that the raw material source influences the optical performance of the glass. Overall, this research highlights the potential of tuning dopant concentration and utilizing sustainable raw materials to enhance the optical characteristics of phosphate glass for use in UV-blocking, optoelectronic, and sensor applications.

Hydrostatic Mass of Galaxy Clusters within Eddington-inspired Born Infeld Theory Modified by Generalized Uncertainty Principle Apryandi, Feri; Ariantara, Raden Giovanni; Pattersons, Muhammad Lawrence
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.01

The mass of galaxy cluster systems can be determined by calculating the hydrostatic equation for such systems. In this study, we derive the hydrostatic mass of galaxy cluster systems within the Eddington-inspired Born-Infeld (EiBI) theory, a modified theory of gravity. The EiBI theory is further modified by incorporating the generalized uncertainty principle (GUP) into its formulation. The GUP affects the mathematical expression of the temperature in galaxy clusters, leading to modifications in the clusters' equation of state (EoS), which is also an essential mathematical tool in hydrostatic equation calculations. This incorporation is motivated by the need to explore quantum gravitational effects on cosmological scales, bridging a fundamental gap between a modified theory of gravity and quantum mechanics. This work is significant in that it introduces the effect of the GUP, implemented through a modification of the temperature, within the framework of EiBI gravity. Using the derived formulation, we calculate the mass of 12 galaxy clusters and compare the results with observational data. The calculations reveal a significant reduction in the masses of these galaxy clusters to the order of 10-19 M⊙. A result which is profoundly inconsistent with observational data, thereby challenging the physical viability of this specific EiBI-GUP framework for modelling large-scale structures like galaxy clusters.

Short-Term Variability of Hα Emission Line Parameters in π Aqr as a Be Star Ramadhan, Taufieq Zannata; Aprilia
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.02

B-emission (Be) star is a B type star which shows emission line in its spectrum, especially Hα, caused by the disk surrounding it. One of the Be stars, π Aqr, is a binary Be star in constellation Aquarius which shows variability of double-peaked Hα emission line caused by a circumstellar disk around the primary component. We aim to study recent physical phenomenon which occurs in the disk of π Aqr star based on its spectral data from 2004 to 2024, retrieved from BeSS database, by analyzing the variability of its Hα emission line parameters: the Violet-to-Red peak ratio (V/R), Emission-to-Continuum ratio (E/C), Equivalent Width (EW), Full Width at Half Maximum (FWHM), and peak separation. The variation of V/R ratio from 2004 to 2019 shows period of 84.1 days which corresponds with orbital period of the binary system. However, in 2024, the V/R variability does not show similar cycle period in previous years as the red peak strength dominates throughout most of the year. The EW and E/C increase, indicating rising disk activity and expansion until 2024. Overall increase of red and blue peak separation roughly suggests expansion in Hα region in the disk.

Comparative Study of Activation Functions and Image Resolution on ResNet-34 for Spiral Galaxy Spin Classification Arwinata, Hafiz Indra; Kusuma, Sultan Hadi; Jaelani, Anton Timur
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.03

This study investigates the application of the Residual Network (ResNet-34) architecture for classifying spiral galaxy spin directions, specifically focusing on the comparative performance of activation functions and cross-dataset generalizability using data derived from the Dark Energy Spectroscopic Instrument Legacy Survey (DESI LS) and the Hyper Suprime Cam Subaru Strategic Program (HSC-SSP) surveys. The methodology ensures robustness by training each model configuration across 10 independent runs. The results demonstrate the clear superiority of the Rectified Linear Unit (ReLU) over the Hyperbolic Tangent (Tanh); ReLU-based models achieved a mean peak accuracy of 94.7% and required only less than 60 epochs to converge, significantly faster than Tanh's 120 epochs. Crucially, we found that models trained on lower-resolution DESI LS images exhibited superior robustness and generalizability compared to high-resolution-trained models, suggesting that low-resolution training acts as effective implicit regularization. This research provides critical design recommendations for efficient machine learning pipelines, particularly for upcoming facilities like the 3.8-meter telescope at Timau National Observatory (TNO), ensuring model stability and transferability across diverse survey conditions.

Comparative Study of the Incorporation of Gold and Silver Nanoparticles into N-719 Dye on the Performance of Dye-Sensitized Solar Cell (DSSC) Putri, Hawinda Restu; Hun, Hilarius Donatus; Rahayu, Setiya; Herman; Pambudi, Muhammad Tegar; Wulandari, Priastuti
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.04

The Dye-Sensitized Solar Cell (DSSC) is a promising third-generation solar cell technology with very significant enhancement in device efficiency. The modification in the fabrication of DSSC is still being studied today in order to increase the stability and lifetime of the devices. The aims of our research is to compare the incorporation of gold and silver nanoparticles capped with 3-Mercaptopropionic Acid (AuMPA or AgMPA) into N-719 dye to enhance DSSC performance. Metal nanoparticles exhibit a unique optical property called Localized Surface Plasmon Resonance (LSPR), which maximizes light absorption. In our experiment, AuMPA and AgMPA were prepared using the chemical reduction method and then incorporated into the dye solution and then in the DSSC assemble, the electrode-TiO2 layer were immersed into dye contained NPs solution. Optical characterization, including absorbance and photolumine-scence spectra, shows a blue shift in the spectral position and an overlap between the intrinsic peak of N-719 and the plasmonic peak of AuMPA or AgMPA, indicating a stable nanoparticle dispersion within the dye matrix. Fourier Transform Infrared (FTIR) spectra confirm the chemical interaction through the changes in the S-H and -COOH vibrations. Scanning Electron Microscopy (SEM) observation reveals the presence and growth of AuMPA and AgMPA nanoparticles within the mesoporous TiO2 layer. The addition of AuMPA into the dye solution increases the PCE of the device from 3.32% to 4.19%, while AgMPA yielded a PCE of 3.76%. Enhancement of our DSSC performance is attributed to the LSPR effect, which enhances light absorption and charge transport. The better performance by the addition of AuMPA into the dye is attributed to a highly substantial plasmonic effect and stability, while AgMPA tends to aggregate, limiting its effectiveness.

Gravitational Lens Parameters Estimation at Intermediate Redshifts Using Convolutional Neural Networks Setiawan, Muhammad Doni; Jaelani, Anton Timur
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.05

Strong gravitational lensing serves as a powerful astrophysical probe, enabling studies of dark matter, galaxy structure, and cosmological parameters. The number of strong gravitational lensing candidates at the galaxy scale is expected to reach O ~ 5 with ongoing and future wide-field galaxy surveys. Current modeling techniques largely rely on conventional fitting methods, such as least squares or maximum likelihood using Markov Chain Monte Carlo, which despite their effectiveness, are computationally expensive and require manual inspection. This motivates the development of faster yet accurate parameter estimation techniques. In this work, we construct a representative training dataset and develop an efficient Convolutional Neural Network to estimate lens parameters: the Einstein radius, axis ratio, and position angle. We utilize data from Public Data Release 3 of the Hyper Suprime-Cam Subaru Strategic Program, selecting lens galaxies in the range 0.3 ≤ z ≤ 0.9 based on the strong-lens probability distribution. We find that the choice of loss function and regularization strategy is critical. To enhance model generalization, we leverage SpatialDropout, which outperforms standard methods by addressing the spatial correlation inherent in convolutional features. Furthermore, prediction accuracy and convergence speed are strongly affected by the distribution of the training data, highlighting the importance of an appropriate loss function. Our optimized model demonstrates robust performance, achieving a Mean Absolute Error of 0.092 arcsec for the Einstein radius, providing a scalable framework for automated analysis in future wide-field surveys.

Aquifer Assessment in the Capit Urang Tourist Area, Metro City: A Vertical Electrical Sounding Approach Sihombing, Josua Nico Batistuta; Hendriyastama, Kemas Daffa; Sipahutar, Andreas; Antosia, Risky Martin
Spektra: Jurnal Fisika dan Aplikasinya Vol. 11 No. 1 (2026): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 11 Issue 1, April 2026
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.111.01

This study was conducted in the Capit Urang Tourist Area, Metro City, which is surrounded by rivers and faces problems with turbid well water that cannot be directly used. The research aims to identify subsurface conditions, especially aquifer thickness and depth, and to evaluate the possibility of deeper aquifers with better water quality. The Vertical Electrical Sounding (VES) method with a Schlumberger array was applied at six sounding points with a maximum AB/2 spacing of 100 m. Data were acquired using a Naniura resistivity meter, processed into apparent resistivity, and inverted with IPI2Win software. The results indicate four main subsurface layers with a resistivity pattern of ρ₁ < ρ₂ > ρ₃ < ρ₄. The first layer has a resistivity of 50–150 Ωm and is interpreted as topsoil with a thickness of less than 1.5 m. The second layer has a resistivity of 300–400 Ωm and is interpreted as gravel to a depth of about 6 m. The third layer, with resistivity of 40–70 Ωm, is interpreted as sandstone functioning as an aquifer with a thickness of 10–13 m to a depth of roughly 16 m. The fourth layer, with resistivity of 160–650 Ωm, is interpreted as impermeable bedrock. The aquifer is influenced by river infiltration, leading to turbid groundwater, while the limited electrode span prevented detection of deeper aquifers. Based on lithological interpretation, the aquifer system is classified as an unconfined to semi-unconfined aquifer. These findings provide a scientific basis for groundwater management and for future hydrogeophysical and hydrochemical investigations to improve water-supply sustainability in the Capit Urang Tourist Area.

Calibration of Dissolved Oxygen Sensors in IoT Systems for Water Quality Monitoring in Aquaculture Mindara, Gema Parasti; Sholihah, Walidatush; Novianty, Inna; Fathonah, Lathifunnisa; Marcelita, Faldiena; Siskandar, Ridwan; Ariyanto, Dodik; Widodo, Bayu; Setiawan, Aep; Firdaus, Naufal Rizqullah
Spektra: Jurnal Fisika dan Aplikasinya Vol. 10 No. 3 (2025): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 10 Issue 3, December 2025
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/SPEKTRA.103.06

Dissolved Oxygen (DO) is an important parameter for maintaining water quality in aquaculture systems. The accuracy of DO sensors significantly affects the reliability of Internet of Things (IoT)-based monitoring systems. This study aimed to calibrate the DO sensor using a two-point calibration method and evaluate the accuracy of the sensor readings compared with those of a reference device (standard DO meter). A key novelty of this study lies in its multi-media calibration, performed directly on six distinct aquaculture water types, providing field-realistic validation conditions not commonly explored in previous studies. Furthermore, the accuracy of the calibrated sensor is evaluated quantitatively using MAE, RMSE, and percentage deviation to ensure rigorous performance assessment. The system was developed using an ESP32 microcontroller, DO sensor (SEN0237), DS18B20 temperature sensor, and ADS1115 ADC module. Testing was performed on six types of aquaculture water media and compared with a standard DO meter using a comparative approach. In total, n = 6 field measurement points (one stabilized reading per water medium) were used to compute MAE, RMSE, and percentage deviation. The comparison results showed that the calibrated sensor had high accuracy, with a Mean Absolute Error (MAE) of 0.1083 mg/L and a Root Mean Square Error (RMSE) of 0.2654 mg/L. Significant deviations occurred only in one type of water medium, whereas the other five showed results consistent with the reference device, indicating stable sensor readings. These findings confirm that proper calibration can improve the accuracy and reliability of IoT systems used for water-quality monitoring. Regular calibration is required to maintain the sensor performance, particularly for long-term use in dynamic aquaculture water environments.

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