JURNAL ILMU FISIKA | UNIVERSITAS ANDALAS

Monte Carlo Simulation to Understand the Working Mechanism of The Electrolytes Lithium Hexafloorophosphate and Ethylene Carbonate

Ego Srivajawaty Sinaga — 2025-09-20

Monte Carlo (MC) simulations provide a powerful approach to investigate electrolyte–electrode interactions and to optimize battery design. This study aims to determine the entropy and average energy of a lithium salt–ethylene carbonate (EC) system, as these parameters are essential for evaluating the Boltzmann factor. The Boltzmann factor was derived from entropy concepts and the principle of maximum entropy, which involves the Boltzmann constant (k) and the number of accessible states (Ω). Simulations were performed using Lennard–Jones parameters within a canonical ensemble framework to compute entropy and energy for systems with varying atom numbers. Results show that the system entropy for two atom types (200 atoms) was 6.67 × 10⁷ kJ·mol^–1·K^–1. For three atom types (300 atoms), the equilibrium entropy reached 1.1 × 10¹⁰ kJ·mol^–1·K^–1, and for four atom types (400 atoms), 1.3 × 10¹³ kJ·mol^–1·K^–1. When reduced to five atom types with only 300 atoms (to minimize computational cost), the entropy was 2.4 × 10⁸ kJ·mol^–1·K^–1. The simulations, employing the Metropolis criterion, successfully identified globally stable configurations, providing new insights into entropy-driven behavior in lithium battery electrolytes.

Equilibrium Points and Periodic Orbits of Artificial Satellite Adjacent to an Oblate and Rotating Asteroid

La Fatsa Fauzia — 2025-10-05

Asteroids have various shapes (mostly irregular) and physical characteristics. Space missions to asteroids are becoming frequent, and a global mapping scheme is applied to collect the asteroids’ physical properties. Depending on the mission purposes, the mapping scheme can encircle the whole asteroid’s body or utilize the asteroid’s equilibrium points for the least energy consumption. Furthermore, it is essential to construct optimal trajectories to maximize the coverage and science results. Thus, an efficient mission can be achieved by devoting periodic orbits of artificial satellites around the equilibria. This study aims to construct periodic orbits related to the equilibria of an oblate shape and rotating asteroid, under the influences of gravitational and rotational potentials. Equations of motion of the satellite affected by the potentials are formulated in the Cartesian coordinate system. By acquiring mutual zero accelerations (first derivative of the potentials with respect to all directions), the equilibria are then obtained. Adjacent to the asteroid, four equilibria were revealed, and analysis of their stability showed that all of them are unstable. Despite this, some periodic orbits centered at the respective equilibria were successfully constructed using some arbitrary parameters (harmonics) that affect the coverage area for mapping the asteroid.

Effect of Freshwater and Seawater Immersion on Mechanical Properties and Pre-Immersion Magnetic Response of Silicone Rubber–Magnetite Composite Magnets

Wibowo Wibowo — 2025-10-05

Magnetite (Fe₃O₄) and RTV 48 silicone rubber-based magnetic composites have potential for outdoor applications due to their flexible and tunable magnetic properties. This study investigates the effect of immersion for 14 days in fresh water and seawater on its mechanical, magnetic, and thermal properties. Specimens were made by mixing 70 wt% Fe₃O₄ powder into RTV 48 matrix, then tested for hardness using Shore A durometer, magnetic properties using Vibrating Sample Magnetometer (VSM), and thermal stability using Thermogravimetric Analysis (TGA). Results showed a decrease in surface hardness due to matrix degradation by water penetration. The magnetic properties continued to exhibit soft magnetic characteristics with low coercivity and remanence. TGA analysis revealed changes in thermal degradation patterns, signaling chemical interactions between the material and the wet environment. These findings suggest that exposure to water can affect the long-term performance of Fe₃O₄-RTV 48 composites, making moisture resistance an important aspect for their outdoor applications.

Enhancing Stellar Orbit Accuracy through the Radius Power Law Time Step Function Model

Hasanuddin Hasanuddin — 2025-10-09

Accurately determining stellar orbits within astrophysical systems is paramount for understanding celestial mechanics. This study proposes a novel approach to enhance orbit accuracy by incorporating a radius power law time step function model. The methodology involves the numerical integration of the system's dynamics using a forward fourth-order symplectic integrator, combined with a time step function dependent on the distance of the test particle from the system's center. We conduct simulations on various astrophysical scenarios represented by conservative potentials, including point mass, Plummer, and Hernquist models. Our results demonstrate that employing a power-law time step function with an exponent of 1.5 significantly reduces phase-space error (measured by the ratio of radial to orbital periods) and improves orbit accuracy (measured by the gradient of the relative total energy drift). The method is easy to implement, computationally efficient, and adaptable to N-body and more general dynamical systems. Its solid theoretical basis and numerical reliability make it a practical tool for improving orbit accuracy in diverse astrophysical applications.

Analysis of Breast Cancer Radiation Dose Distribution Using Bolus Density in 3DCRT Technique Radiotherapy Planning at Andalas University Hospital

Dini Asetiyo — 2026-02-11

Analysis of breast cancer radiation dose distribution using bolus density in radiotherapy planning of the Three-Dimensional Conformal Radiotherapy (3DCRT) technique has been conducted. This research aims to analyze radiation dose distribution in breast cancer patients using bolus density in radiotherapy planning of the 3DCRT technique. Five images of breast cancer patients were processed using TPS Eclipse software. The bolus density values used were a mixture of beeswax and petroleum jelly, playdough, silicone rubber, and 3D Polylactic Acid. CI and HI values were calculated based on the International Commission on Radiation Units and Measures (ICRU) Reports 62 and 83. Radiation dose in OAR was verified based on the Quantitative Analysis of Normal Tissue Effect in the Clinic (QUANTEC) standard. The results showed that all four bolus densities can be used in breast cancer patients, with CI values the CI value ranges from 0.93 to 0.98 by ICRU Report 62 standards and HI values close to ICRU Report 83 standards. In cardiac OAR, one patient exceeded the QUANTEC standard, while for lung OAR, all patients were below the QUANTEC standard. Using bolus density provides optimal radiation dose distribution on breast cancer targets.

Long-Term Crustal Deformation along the Southern Java Subduction Margin Revealed by GNSS Observations

Vira Friska — 2026-02-23

This study examines long-term GNSS-derived velocities along southern Java during 2011–2020 to characterize regional crustal deformation. Data from six InaCORS stations operated by BIG were processed using GAMIT/GLOBK to produce time series and estimate horizontal and vertical velocities. Horizontal velocities range from 21.35 mm/yr to 27.54 mm/yr toward the southeast, reflecting strong Eurasian Plate influence. The time series indicates gradual, continuous displacement without significant co-seismic offsets, despite several Mw ~6 earthquakes in the region. Vertical velocities show both uplift and subsidence, ranging from −13.84 mm/yr to 12.61 mm/yr, likely resulting from combined tectonic and non-tectonic processes. Because vertical GNSS measurements generally have higher uncertainty, these results must be interpreted cautiously. Although station motions appear stable, this does not indicate low seismic hazard. Instead, it may suggest ongoing strain accumulation within a seismic gap that could generate a future major earthquake. Overall, these findings enhance understanding of southern Java’s subduction dynamics and support improved earthquake hazard assessment and disaster preparedness.

Structural Interpretation of the Jonggol Mount Area, Kulon Progo, Yogyakarta, Using Gravity Inversion Modelling

Setyo Pambudi — 2026-02-25

The Mount Jonggol region in Kulon Progo, Yogyakarta, constitutes an important segment of the Sunda–Banda magmatic arc system; however, its subsurface structural configuration remains insufficiently understood. This study aims to interpret subsurface structures and lithological boundaries through derivative analysis and three-dimensional gravity inversion modelling. The gravity dataset was obtained from the Global Gravity Model Plus (GGMplus), which provides absolute gravity acceleration measurements with high spatial resolution. The data were processed using sequential corrections, including normal gravity, free-air, simple Bouguer, and terrain corrections, to generate the Complete Bouguer Anomaly (CBA). The resulting CBA data were analyzed using the First and Second Horizontal Derivative (FHD and SHD) methods to delineate structural discontinuities, fault planes, and density contrasts. Furthermore, three-dimensional inversion modelling was conducted to visualize subsurface density variations to a depth of approximately 3.5 km. The results indicate that Mount Jonggol is situated at the tectono-lithological boundary between the low-density Jonggrangan Formation (2.0–2.4 g/cc) and the high-density Old Andesite Formation (2.7–3.0 g/cc). The gravity anomaly pattern reveals a northwest–southeast-oriented magmatic corridor controlled by thrust and strike-slip fault systems, providing important insights into the tectono-magmatic evolution and uplift mechanisms of southern Central Java.

A Computational Physics–Based Machine Learning Modelling of Multiphase Flow Dynamics for Crude Oil Percentage Prediction Using Water Cut and Sediment Indicators

Jesi Pebralia — 2026-03-01

Existing crude oil percentage prediction methods often rely on direct measurements and historical data, neglecting the coupled multiphase characteristics of oil–water–sediment systems, which limits predictive accuracy. This study develops a computational physics–based machine learning model integrating key multiphase production parameters, including water cut, basic sediment, and BS&W, using samples from PT. Pertamina Puspa Field Jambi. Data were split into two sets: one for model development and one for validation to prevent overfitting. Linear Regression, Support Vector Machine (SVM), and Random Forest algorithms were applied, with Linear Regression achieving the best performance. For the test dataset, the model yielded a Mean Absolute Error of 0.022168, a Mean Squared Error of 0.001227, and an accuracy of 0.99877, demonstrating precise capture of multiphase interactions. The proposed computational physics–based modelling framework provided improved predictive reliability and consistency. Correlation analyses indicated a coefficient of determination (R²) of 0.99 and a perfect negative correlation (r = −1) between BS&W and oil content, showing that higher BS&W corresponds to lower oil percentage. This framework offers improved predictive reliability and consistency for crude oil quality assessment.

Hierarchical Tissue-Based MRI Features with Explainable Machine Learning for Alzheimer’s Disease Classification

Muhammed B Ceesay — 2026-03-01

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by multiscale structural brain degeneration. Many MRI-based machine learning approaches rely on coarse volumetric measures or black-box models with limited anatomical interpretability. This study aims to localize anatomically meaningful brain regions that discriminate AD from cognitively normal (CN) subjects using a hierarchical tissue-based (HTB) MRI framework. The method models gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) volumetric changes at lobar, gyral, and 246 fine-grained subregions defined by the Brainnetome atlas. T1-weighted MRI scans from 454 participants (227 AD, 227 CN) obtained from ADNI and MIRIAD were preprocessed using AC-PC alignment, N4 bias correction, skull stripping, and nonlinear registration to MNI space. A total of 561 HTB features were extracted to train Random Forest and XGBoost classifiers using five-fold stratified cross-validation with Bayesian hyperparameter optimization. The XGBoost model achieved the best performance (Accuracy: 79.74%, ROC-AUC: 85.07%), comparable to recent atlas-based MRI classification studies, while providing improved multiscale anatomical interpretability. SHAP analysis revealed consistent hierarchical atrophy patterns in hippocampal subregions, medial amygdala, and areas 35/36 and 28/34, demonstrating that hierarchical anatomical modeling with explainable machine learning enables transparent localization of clinically meaningful AD biomarkers without reliance on black-box architectures.

Dynamics of Extreme Drought and Extreme Wet in Indonesia: Analysis of Frequency, Trends, and Spatial Distribution 1995–2024

Suhadi Suhadi — 2026-03-04

The climatological pattern of rainfall and the occurrence of extreme drought and extreme wet in Indonesia are influenced by monsoon dynamics, topography, and Sea Surface Temperature Anomalies (SSTA) in the Pacific and Indian Oceans. Although studies on extreme droughts in Indonesia exist, none have quantified the spatial frequency of extreme drought and rainfall events. This study aims to determine the frequency and trend of extreme drought and extreme rain in Indonesia during 1995–2024. Gridded precipitation data from the Global Precipitation Climatology Center (GPCC) with 0.5° resolution were used. Frequencies of extreme drought and extreme wet were calculated using the Standardized Precipitation Index (SPI), while trends were estimated from the Poisson Regression slope. Frequency and trend were computed for the grid to represent spatial distributions. SPI results at 3, 6, and 12-month scales show Sumatra, Kalimantan, and Papua experienced extreme droughts 8–12 times, with varying frequencies. Extreme droughts were widespread in eastern Indonesia during the dry season (JJA and SON), with longer persistence in SPI-6 and SPI-12. In contrast, extreme wet events occurred more frequently in western and central Indonesia, during the rainy season (DJF), when the western monsoon transported moisture from the Indian Ocean.