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INDONESIA
BULETIN FISIKA
Published by Universitas Udayana
ISSN : 14114690     EISSN : 25809733     DOI : https://doi.org/10.24843/BF
Core Subject : Health, Science,
Astronomy Energy Materials Science & Nanotechnology Medicine & Pharmacology Physics
Aims and Scope Aims The Journal aims to promote the theory and application in the field of physics and to encourage a vigorous dialogue among scholars and researchers worldwide. It presents original research articles, letters, and review articles, and publishes the latest achievements and developments in physics and related fields. All contributions shall be rigorously refereed and selected based on the quality and originality of the work as well as the breadth of interest to readers. Accepted papers will immediately appear online. The Journal welcomes contributions that the manuscript is written in Indonesian or English. Scope The scope of this journal covers pure and applied physics. The topics include advanced material, optoelectronics, laser applications, biophysics, medical physics, instrumentation, geophysics, environmental physics, and related fields.
Arjuna Subject : Fisika dan Astronomi - Fisika dan Astronomi (Lain-Lain)
Articles 38 Documents
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Machine Learning to Predict Climate Change in Coastal Areas of Indonesia Huriyatul Firdausi; Melly Ariska; Sardianto Marcos Siahaan; Hamdi Akhsan; Yenny Anwar; Iin Seprina; Taufiq Taufiq
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p05

Abstract

Indonesia's coastal regions face significant threats from climate change, including rainfall uncertainty, rising temperatures, and sea level rise. This study aims to explore the potential of machine learning algorithms in predicting climate parameter changes in the coastal areas of Minangkabau, Pesawaran, and Maritim Panjang. Daily climatological data obtained from the Meteorology, Climatology, and Geophysics Agency (BMKG) were used as the basis for model training. Three primary algorithms were tested Random Forest, XGBoost, and Long Short-Term Memory (LSTM) selected for their capability to handle complex and temporal data. The research methodology included data preprocessing, model training, cross-validation, and predictive performance evaluation using metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the coefficient of determination (R²). Preliminary results show that LSTM excels in time series prediction, while XGBoost offers a good balance between speed and accuracy. These findings indicate that machine learning-based approaches have strong potential as decision-support tools for climate change mitigation and adaptation planning in Indonesia’s coastal regions.
Analysis of Atmospheric Dynamics and Sea Surface Temperature as Potential Indicators of Rainfall Occurrence in West Kalimantan Province during 2022–2023 Nadia Fithriana; Wirastuti Widyatmanti; Emilya Nurjani
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p06

Abstract

West Kalimantan Province, crossed by the equator, has a tropical climate characterized by almost year-round rainfall and relatively high average air temperatures. This condition is also accompanied by the emergence of numerous hotspots. These two climate characteristics appear contradictory, likely related to rainfall distribution patterns in the region. The purpose of this study is to analyze rainfall potential in West Kalimantan Province based on atmospheric and ocean dynamics. The data used include satellite imagery and reanalysis of each parameter: sea level pressure, wind, sea surface temperature, and altitude in 2022-2023. The analysis method is applied descriptively through plot interpretation to illustrate the data distribution and the relationships between parameters. Rainfall distribution in West Kalimantan Province is influenced by global climate dynamics and topographic conditions. In 2022, with La Nina and the southwest monsoon, rainfall was high and evenly distributed, while in 2023, with El Nino and the east monsoon, rainfall decreased, especially on the coast. The mountainous areas still receive rainfall throughout the year, although the intensity is reduced.
Identification Of Peat Soil Thickness Using The Geolectrical Resistivity Method (Case Study: Parit Demang Dalam Road, Pontianak City) Bella Ankara Can; Zulfian Zulfian; Joko Sampurno
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p04

Abstract

Parit Demang is an area with peatland used for residential purposes, so information on soil thickness in this area is very important for development planning. This study aims to identify peat soil thickness using the Wenner-Schlumberger configuration of the geoelectric method. Data was obtained through three measurement lines, each 50 m long. The 2D inversion modeling at the study site showed that the resistivity values of the peat layer ranged from 32.4 to 315 Ωm, with peat soil thickness between 2.3 to 5.5 m. The interpretation results were validated with soil sample drilling data. The layer located under the peat soil was identified as clay with resistivity between 1.56 to 15.2 Ωm. Information on peat soil thickness can be used as a basis for selecting soil improvement methods by the local community and related parties for development planning, particularly in the process of house construction.
Identification of Peat Soil Thickness Using the 2D Electrical Resistivity Method: Case Study Bansir Darat Subdistrict, Pontianak City Dwi Ishika Noviandita; Zulfian Zulfian; Joko Sampurno
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p11

Abstract

Bansir Darat is a sub-district that utilizes peatland for residential areas. Therefore, information about peatland thickness is essential for the community in the sub-district. This study aims to identify the thickness of peatland in the Bansir Darat sub-district. The geoelectric resistivity method using the Wenner-Schlumberger configuration was used in this measurement. Data collection was carried out on three tracks with a length of 50 m each and the smallest electrode spacing of 2 m. The obtained field data were inverted using the Least Squares Inversion method. The inversion results in the form of a resistivity cross-section with peatland soil estimated to have a resistivity value of 0.687 - 24.2 Ωm. The interpretation results indicate that the thickness of the peatland varies between 1.5 - 6 m. Information regarding the thickness of the peatland can be used in planning residential development by the local community.
Synthesis and Characterization of Activated Carbon from Jackfruit Banana (Musa paradisiaca L.) Leaves as Supercapacitor Electrode Material Satria Ulia Uliana; Bidayatul Armynah; Emar Mokiman Kala’Tagari
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p01

Abstract

A study was conducted to determine the maximum carbonization temperature for producing activated carbon derived from banana leaves (Musa paradisiaca L.) as electrode material for supercapacitors with KOH activation. Activated carbon was prepared using a chemical activation method with 0.5 M KOH at carbonization temperatures of 750, 800, and 850 °C under a CO₂ atmosphere. Thermogravimetric (TG) and Derivative Thermogravimetric (DTG) analyses revealed the highest thermal degradation rate at 313.3 °C, indicating the temperature range with the most rapid mass loss. Density analysis showed that the density of activated carbon decreased with increasing carbonization temperature. Fourier Transform Infrared (FTIR) characterization confirmed the presence of carbon bonds, while X-Ray Diffraction (XRD) patterns indicated a mixed amorphous–semi-crystalline structure. Scanning Electron Microscopy (SEM) analysis revealed a surface morphology with more uniformly distributed and open pores, indicating enhanced pore development with increasing carbonization temperature. Energy Dispersive X-ray Spectroscopy (EDS) confirmed the dominance of potassium, accounting for 73.77 wt% and 49.80 at%. Electrochemical evaluation showed that the specific capacitance exhibited only slight variations across the tested carbonization temperatures, with the highest value of 209 F/g obtained at 850 °C. These results indicate that 850 °C is the maximum carbonization temperature to produce high-performance activated carbon from banana leaves, reinforcing its potential as a sustainable material for supercapacitor applications.
Analysis of the Hydrodynamic Characteristics of Limboto Lake Waters Based on Momentum Fluxes Mikail Gabriel Khan Khan; Raghel Yunginger Yunginger; Dewa Gede Eka Setiawan; Mohamad Jahja; Icha Untari Meidji; Haerul Ahmadi; Cucu Kusmayancu; Merpati Teodoris Nalle
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p02

Abstract

The waters of Lake Limboto show a decline in water quality, characterized by a decrease in clarity. Environmental factors, such as wind speed and direction, play a significant role in influencing the dynamics and quality of lake waters. To understand the influence of wind on water conditions, a comprehensive hydrodynamic study is required. This study focuses on analyzing the hydrodynamic characteristics of Lake Limboto waters based on momentum flux and its implications for lake water conditions. Wind speed and direction measurements were conducted on seven ducks in Lake Limboto waters during the period of November 1-3, 2024. Data were collected in the morning, afternoon, and evening. The lake's hydrodynamic characteristics were determined using formulas from the measured data. Hydrodynamic characteristics were interpolated using IDW cross validation leave one out and optimized with rank and neighboring point parameters. Wind direction was interpolated using IDW and converted into a vector field using Vector Field Layer Manager. It was found that the momentum flux by wind in Lake Limboto waters has a value range of 0-0.05 N/m2, and cross validation produced an RMSE of 0.003-0.01 N/m2. The interaction of momentum flux from wind and river flow causes sediment to be deposited in the coastal area of ​​Lake Limboto.
Development of an Incinerator with a Multi-Stage Condenser System as an Effort to Reduce CO₂ Emissions Gas from Plastic Waste Burning in Gorontalo City Raghel Yunginger; Yusuf Usman; Meilan Demulawa; Salmawaty Tansa; Mohamad Jahja; Muhammad Yunus
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p03

Abstract

The increasing plastic waste volume in Gorontalo City is not balanced by a good management system, making people choose to burn their waste in open space. Not only makes a bad scene, this burning emits dangerous gases such as CO2 that contributes to poor air quality and climate change. This study has developed an environmentally friendly incinerator with a stacked condenser system that emits less CO2 gas. This incinerator consists of three main components: a combustion zone, as the place where plastic waste is burned; a chimney, for the flowing of gas; and stacked condensors, for cooling and keeping the gas before emitting it out. We test the incinerator with and without condensors based on the CO2 emission from 20 minutes' burning of 1.5 kg of plastic waste. The results show that an incinerator with a stacked condensor system can significantly reduce CO2 gas emissions by 18.88% more than an incinerator without condensors. This implies that incinerator with stacked condensors can be an alternative way to reduce CO2 gas from open-space waste burning on a small scale.
Analysis of Earthquake Hazard-Prone Areas Using Peak Ground Acceleration (PGA) Values in Enggano Island, Bengkulu Hangga Novian Adi Putra
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p09

Abstract

Enggano Island is one of the oceanic islands located on the outermost edge of Bengkulu Province, which makes it highly vulnerable to tectonic earthquake hazards. This study aims to analyze the level of earthquake hazard vulnerability in the Enggano Island region of Bengkulu Province by utilizing Peak Ground Acceleration (PGA) values as the main indicator for assessing earthquake hazard potential. This study was conducted using 37 earthquake events data that occurred in the vicinity of Enggano Island within the time span from 1990 to 2025. The earthquake data used in this analysis focused on events with a magnitude of 4 Mw or higher and depth less than 50 km. Based on the disaster vulnerability analysis in the Enggano Island area, the regions with the highest earthquake hazard levels are Banjar Sari, Meok, Malakoni, and also a portion of Apoho, which have a PGA range of 106 gal to 114 gal and VI MMI scale. The moderate hazard levels are upper parts of Banjar Sari, Meok, Apoho, and Malakoni, as well as the southern portions of Kaana and Kahyapu, which have a PGA range of 94 gal to 104 gal and VI MMI scale. In contrast, the areas with lower hazard levels are found in the northern parts of Kaana and Kahyapu, where the PGA ranges from 78 to 92 gal and corresponds to intensity level V on the MMI scale. This study indicates that Enggano Island falls within a moderate earthquake hazard category.
The Corrosive Properties Analysis of Biodegradable Magnesium Composites Mg-xCAp (x=0, 5%, 10%, and 15%) for Bone Implant Applications Ana Bano; Ni Nyoman Rupiasih; Iwan Setyadi; Mirza Wibisono; Suryadi Suryadi; I Nyoman Jujur
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p08

Abstract

Magnesium (Mg) is a promising biodegradable material for bone implant applications due to its suitability of mechanical properties and biocompatibility with natural bone. However, its rapid degradation in physiological environments remains a major obstacle in clinical applications. The addition of carbonated apatite (CAp) as a bioactive reinforcing phase is expected to improve the corrosion resistance of Mg-based composites by forming a more stable surface layer. This study aims to evaluate the corrosion properties of Mg–xCAp composites with variations in CAp content of 0%, 5%, 10%, and 15%. Corrosion testing was carried out electrochemically in simulated body fluid (SBF) solutions using the Open Circuit Potential (OCP), Electrochemical Impedance Spectroscopy (EIS), and Tafel polarization methods. The OCP results showed a potential shift towards a more positive direction up to −1.87 V as the CAp fraction increased, indicating increased electrochemical stability. EIS analysis showed a progressive increase in charge transfer resistance (Rct), with the highest value of 309.8 Ω•cm² in the Mg–15CAp composite, indicating the formation of a more protective surface layer against aggressive ion penetration. Tafel polarization results confirmed a significant decrease in corrosion rate, with Mg–15CAp showing the lowest corrosion rate of 2.03 mm/year. Overall, the addition of CAp proved effective in controlling Mg degradation and improving the corrosion resistance of the composite, thus potentially expanding the application of Mg–CAp as a biodegradable bone implant material.
Impact of Training Dataset Size on the Accuracy of L-SVR Single-Time-Point Renal Dosimetry for [¹⁷⁷Lu]Lu-PSMA-617 Therapy Abdurrahman Aziz Wicaksono; Jaja Muhammad Jabar; Syahril Siregar; Deni Hardiansyah
BULETIN FISIKA Vol. 27 No. 1 (2026): BULETIN FISIKA
Publisher : Departement of Physics Faculty of Mathematics and Natural Sciences, and Institute of Research and Community Services Udayana University, Kampus Bukit Jimbaran Badung Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/BF.2026.v27.i01.p07

Abstract

Radiopharmaceutical therapy (RPT) using [¹⁷⁷Lu]Lu-PSMA-617 requires accurate dosimetry to evaluate organs-at-risk (OAR), specifically the kidneys. Single-time-point (STP) dosimetry simplifies clinical workflows by reducing SPECT/CT acquisition. Machine learning (ML) offers a potential solution, yet clinical implementation is hindered by the scarcity of sufficient training datasets for ML-based studies. This study investigated the relationship between training dataset size and time-integrated activity (TIA) estimation accuracy. A Linear Support Vector Regression (L-SVR) model was trained on synthetic virtual patients (VPs, 5,000 total) simulated from a published PBMS NLMEM renal biokinetics at five imaging times (t=1.8 h, 18.7 h, 42.6 h, 66.2 h, and 160.3 h). Time-activity-curve (TAC) and reference TIA (rTIA) were calculated for each VP. Random sampling was performed in increasing dataset sizes. Sample sizes were sub-sampled to training (80%) and testing (20%) datasets. L-SVR was trained on STP data at 42.6 h post-injection (best-time-point of PBMS NLMEM study) from the training dataset and tested by generating estimated TIA (eTIA) with input from the testing dataset. Performance was evaluated by calculating root-mean-square-error (RMSE) and mean-absolute-percentage-error (MAPE) of the eTIA to rTIA. Results showed that the accuracy of eTIA from ML STP dosimetry depends on training size: small samples (n=10) yielded poor performance (RMSE>85.98%, MAPE>89.1%). Accuracy improved significantly at n=500 (RMSE=14.07%) and plateaued beyond n=1,000 (peak RMSE=13.07%). Results indicate that the L-SVR model of the study requires sample sizes of n>200, with optimal gains up to n=2,000. This study suggests synthetic data as a methodological bridge between limited clinical datasets and data-intensive ML approaches.

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