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Jurnal Fisika Unand
Published by Universitas Andalas
ISSN : 23028491     EISSN : 26862433     DOI : https://doi.org/10.25077/jfu
Core Subject : Science, Engineering,
Earth & Planetary Sciences Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics
Makalah yang dapat dipublikasikan dalam jurnal ini adalah makalah dalam bidang Fisika meliputi Fisika Atmosfir, Fisika Bumi, Fisika Intrumentasi, Fisika Material, Fisika Nuklir, Fisika Radiasi, Fisika Komputasi, Fisika Teori, Biofisika, ataupun bidang lain yang masih ada kaitannya dengan ilmu fisika.
Arjuna Subject : Fisika dan Astronomi - Fisika Nuklir dan Molekuler, dan Ooptik
Articles 5 Documents
 1 
Search results for , issue "vol 15 no 5 (2026)" : 5 Documents clear
Pengembangan Quality Control Phantom Berbahan Akrilik dan Aluminium Alfieta Rohmaful Aeni; Danang Noeramarullah Yudhistira
Jurnal Fisika Unand Vol 15 No 5 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.5.470-475.2026

Abstract

The high cost of phantoms for diagnostic image quality control presents a challenge, especially for hospitals in remote areas. This study developed a low-cost, simplified phantom using acrylic and aluminum materials. Circular acrylic sheets, each 3 mm thick, were stacked into 10 layers and drilled with 15 holes, each filled with aluminum disks of varying thickness from 1 mm to 15 mm. The phantom was exposed to X-rays using tube voltages of 50 kV, 60 kV, and 70 kV for 5 ms at a tube current of 160 mA. The resulting radiographic images were analyzed using ImageJ to assess grayscale values. Results showed that images obtained at 60 kV provided the best contrast, with clear differentiation of aluminum thicknesses and separation from the background. At 50 kV, aluminum layers thicker than 10 mm were not easily distinguishable due to insufficient X-ray energy, while at 70 kV, thinner layers (1–5 mm) lacked visibility due to over-penetration. These findings suggest that the developed phantom is adequately responsive to exposure parameter changes and has potential for use in basic radiographic imaging evaluations and educational settings.
Interpretasi Geologi Bawah Permukaan Berdasarkan Data Geomagnetik dan GPR di Area Hot Spring Natar - Cisarua, Lampung Trie Hartini; Ira Kusuma Dewi; Syamsurijal Rasimeng; Alimuddin Alimuddin; Rudy Zefrianto Sinambela; Ridho Destawan
Jurnal Fisika Unand Vol 15 No 5 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.5.476-482.2026

Abstract

The geothermal manifestations in the form of hot springs at the Natar Hot Water Resource and the Cisarua hot spring bath are part of a geothermal system that has developed in the Lampung area. This study aims to interpret subsurface geological conditions and to identify structural controls governing the geothermal system within the study area using integrated geomagnetic and Ground Penetrating Radar (GPR) methods. Geomagnetic data processing involved diurnal correction and International Geomagnetic Reference Field (IGRF) correction applied to total magnetic field measurements to obtain Total Magnetic Anomaly (TMA) maps, followed by Reduction to the Pole (RTP) transformation to enhance anomaly positioning over their causative sources. In parallel, GPR data processing was conducted to generate high-resolution images of shallow subsurface structures. The results indicate that the hot spring manifestations are spatially associated with zones of low magnetic anomalies, interpreted as demagnetized rocks resulting from hydrothermal alteration processes. Furthermore, GPR profiles reveal chaotic and discontinuous reflection patterns, which are interpreted as altered zones acting as a cap rock (clay cap) within the geothermal system. The integration of geomagnetic and GPR datasets suggests that hydrothermal alteration and structurally controlled fluid pathways play a significant role in the development of geothermal manifestations in the study area
Analisis Hubungan Massa Tubuh, Compressed Breast Thickness (CBT), Usia dan Faktor Eksposi terhadap Mean Glandular Dose (MGD) pada Pemeriksaan Pasien Pesawat Sinar-X Mamografi di RSUP Dr. M. Djamil Anissa Ledita; Dian Milvita; Ida Bagus Gede Putra Pratama
Jurnal Fisika Unand Vol 15 No 5 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.5.483-489.2026

Abstract

A study on the analysis of the relationship between body mass, compressed breast thickness (CBT), age, and exposure factors on the mean glandular dose (MGD) in mammography X-ray examinations was conducted at the Radiology Department of Dr. M. Djamil Hospital in Padang. The study aimed to analyze the relationship between several parameters and MGD values. The study was conducted using a collection of mammography patient dosimetry data from January to July 2025, comprising 165 data points. The methods used were simple linear correlation and multiple linear regression tests. The results showed that body mass had a positive and moderate relationship with MGD, with a correlation coefficient (rxy) values ranging from 0,322 to 0,383. CBT had a positive and strong relationship with MGD with an (rxy) values from 0,566 to 0,574. Age had a negative and very weak relationship with an (rxy) values ranging from (-0,146) to (-0,037). . Exposure factors had a positive and very strong relationship with MGD with an Multiple R values ranging from 0,993 to 0,995.
Sistem Pendeteksi Area Blind Spot pada Kendaraan Truk Menggunakan Computer Vision dan Sensor Ultrasonik JSN-SR04T Berbasis Internet of Things Fuji Aulia Rahmi; Meqorry Yusfi
Jurnal Fisika Unand Vol 15 No 5 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.5.490-496.2026

Abstract

The rising number of vehicles has led to increased traffic accidents, partly due to blind spot  areas on trucks that block the driver’s view of surrounding objects. This study aims to develop an Internet of Things (IoT)-based blind spot detection system integrating a JSN-SR04T ultrasonic sensor for early warning and computer vision using YOLOv11n on an ESP32-CAM for object detection. The method includes collecting and augmenting an initial dataset of 417 images, training the YOLOv11n model on Google Colab, and designing hardware consisting of the JSN-SR04T sensor, ESP32-CAM, NodeMCU ESP8266, and LED indicators, with MQTT-based communication for real-time monitoring. Position testing shows the highest accuracy in the front position for cars at 93% (142 cm), while the farthest detection distance is achieved for pedestrians in the rear position up to 329 cm (73% accuracy). Speed testing indicates accuracy at 10–20 km/h reaches 100% (car), 90% (motorcyclist), and 80% (pedestrian), then drops at 50 km/h to 70%, 60%, and 50%. The system is effective for early warnings at low to moderate speeds but requires improvement for small objects at high speeds.
Nowcasting Trajektori dan Intensitas Siklon Tropis Seroja Menggunakan Temporal Convolutional Network Pertiwi Setyowati; Yosafat Donni Haryanto; Adi Mulsandi; Latifah Nurul Qomariyatuzzamzami
Jurnal Fisika Unand Vol 15 No 5 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.5.497-504.2026

Abstract

Tropical cyclones have an extremely short detection-to-peak-impact lead time, as exemplified by Tropical Cyclone Seroja, which caused catastrophic damage in East Nusa Tenggara in April 2021, while conventional methods such as the Dvorak technique, the Advanced Dvorak Technique, and Numerical Weather Prediction remain limited in update speed and objectivity. This study applies the Temporal Convolutional Network (TCN) for nowcasting the track and intensity of Tropical Cyclone Seroja as a faster, computationally lighter alternative capable of capturing nonlinear cyclone dynamics. The study uses historical best-track data from the Bureau of Meteorology (BOM) Australia covering 1973–2026 (longitude, latitude, central pressure, wind speed), with the model trained via a sliding-window approach for predictions at 6–24-hour horizons and tested on Cyclone Seroja, evaluated using RMSE, MAPE, and R². Results show TCN performs best in track prediction (longitude and latitude RMSE of 1.01–2.97 and 0.40–1.88, consistently high R² up to 24 hours), whereas intensity performance declines sharply (central-pressure RMSE of 4.01–10.40 hPa, wind-speed RMSE of 2.87–7.22 m/s, wind-speed MAPE up to 23.77%, negative R²), associated with the interaction between Cyclone Seroja and Tropical Cyclone Odette through the Fujiwhara effect. TCN has potential as an alternative to conventional methods for tropical cyclone early-warning systems in Indonesia, particularly for track prediction, with further development needed to improve intensity-prediction accuracy.

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