cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Herri Trilaksana, S.Si, M.Si, Ph.D
Contact Email
herri-t@fst.unair.ac.id
Phone
+6282142563056
Journal Mail Official
iapl@journal.unair.ac.id
Editorial Address
Physics Department, Faculty of Science and Technology, Airlangga University, Kampus C Mulyorejo, Surabaya, 60115
Location
Kota surabaya,
Jawa timur
INDONESIA
Indonesian Applied Physics Letters
Published by Universitas Airlangga
ISSN : -     EISSN : 27453502     DOI : http://dx.doi.org/10.20473/iapl.v1i2.23444
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Electrical & Electronics Engineering Materials Science & Nanotechnology Physics
Indonesian Applied Physics Letter is an multi-disciplinary international journal which publishes high quality scientific and engineering papers on all aspects of research in the area of applied physics and wide practical application of achieved results. The field of IAPL, which can be described as encounter of material science, theoretical science, computational, instrumentation, biomedical, geophysics and applied physics, has become distinguishable integrated discipline of research-based endeavor.
Arjuna Subject : Fisika dan Astronomi - Fisika dan Astronomi (Lain-Lain)
Articles 50 Documents
 1   2   3   4   5 
The Implementation of Channel Area Thresholding in Early Detection System of Acute Respiratory Infection (ARI) Fitri, Zilvanhisna Emka; Imron, Arizal Mujibtamana Nanda
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.55626

Abstract

Acute respiratory infections (ARI) are infectious diseases that affect both children and adults, particularly in the context of climate change. Bacteria are one of the causes of ARI. According to the government, the discovery of the bacteria that cause ARI is an indicator of successful management of infectious diseases. The current obstacle is the limited number of medical analysts, which results in longer microscopic examination times and requires a high level of objectivity. Therefore, a system for the early detection of ARI-causing bacteria was developed using digital image processing techniques, specifically channel area thresholding as one of the segmentation methods. This research employs four shape features for bacterial classification: the number of bacterial colonies, area, perimeter, and shape. The Naí¯ve Bayes intelligent system method is used for the classification process. The system had an accuracy rate of 86.84% in the classification of four types of bacteria: S. aureus, S. pneumoniae, C. diphteriae and M. tuberculosis
EMG Instrumentation Modeling and Feature Processing Based On Discrete Wavelet Transform Zukro Aini, Rasyida Shabihah
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.56245

Abstract

Electromyography (EMG) instrumentation is essential in generating electrical signals from skeletal muscles. EMG sensors are helpful in various cases requiring the detection of human muscle contractions, neuromuscular disorders, and rehabilitation. EMG instrumentation is divided into two parts, namely, the analogue part and the digital part. The EMG instrumentation design comprises a digital-to-analog converter (DAC), instrumentation amplifier, filter, and analog-to-digital converter (ADC). Meanwhile, in digital signal processing adopting the Discrete Wavelet Transform (DWT) method, frequency analysis using DWT has proven superior. It is used in various research and has exceptionally detailed coefficient features for classifying neuromuscular disease signals. Therefore, this research aims to design analogue and digital EMG instrumentation and identify features in the form of detailed coefficients. The data used are two Physionet signals from the anterior tibialis body with myopathy and neuropathy disorders. The results obtained for EMG analogue instrumentation provide the expected results until they reach the filter component stage. The resulting signal forms a block in the filter component, different from the initial EMG signal. Meanwhile, the DWT decomposition results are of the Daubechies4 wavelet type with the highest level 17, which has a high detail coefficient at low frequencies, high dilation and the result of a mixture of neuropathy and myopathy EMG signals, or in other words, at low energies, this result is by the DWT theorem. Determining the efficiency of the DWT detailed coefficient feature requires further study with the same signal subject. The DWT features obtained can then be developed for various needs in EMG signal recognition.
Review of Application YOLOv8 in Medical Imaging Widayani, Aisyah; Putra, Ayub Manggala; Maghriebi, Agiel Ridlo; Adi, Dea Zalfa Cahyla; Ridho, Moh. Hilmy Faishal
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.57001

Abstract

Deep learning has revolutionized medical imaging analysis, with YOLOv8 emerging as a promising tool forvarious tasks like lesion detection, organ segmentation and disease classification. This review investigates YOLOv8'sapplications across diverse medical imaging modalities (X-Ray, CT-Scan and MRI). We conducted a systematic literaturesearch across databases like Pubmed, ScienceDirect and IEEE to identify relevant studies evaluating YOLOv8'sperformance in medical imaging analysis. YOLOv8 achieved high performance for meningioma and pituitary tumorswith and without data augmentation (precision >0.92, recall >0.90, mAP >0.93). Glioma detection showed lowerperformance but still promising results (precision >0.86, recall >0.81, mAP >0.86). Breast cancer detection with SGDoptimizer yielded best performance with an average mAP of 0.87 for mass detection. The model achieved high accuracyin detecting normal (mAP 0.939) and malignant lesions (mAP 0.911). YOLO v8 on Dental radiograph successfullydetected cavities, impacted teeth, fillings and implants (precision of >0.82, recall of >0.78 and F1-Score of >0.80). Lastly,for lung disease classification, YOLOv8 achieved high accuracy (99.8% training and 90% validation) in classifyingnormal, COVID-19, influenza and lung cancer disease. With the importance to improve clinical decision-making andpatient outcomes in healthcare, the YOLOv8 algorthm underscores the importance of pre-processing, augmentation andoptimization of key hyperparameters.
Detection of Throat Disorders Based on Thermal Image Using Digital Image Processing Methods Arisgraha, S.T., M.T., Franky Chandra Satria; Rulaningtyas, Riries; Purwanti, Endah; Ama, Fadli
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.57073

Abstract

Throat disorders are often considered trivial for some people, but if they are not treated immediately they can result in more severe conditions and require a longer time to cure this disorder. Objective, safe and comfortable detection of throat disorders is important because throat disorders are an indication of inflammation which, if not treated immediately, can have negative consequences. This research aims to detect throat disorders based on thermal images using digital image processing methods. Image capture was carried out with the same color pallete range on the camera, namely 33°C-38°C. The image obtained is then cropped in the ROI, then the image is threshold with a gray degree of 190. Pixels that have a gray degree above 190 are converted to white, while those below the threshold are converted to black. Next, the percentage of each white and black area is calculated compared to the total ROI area. If the percentage of white area is greater than 38% compared to the area of "‹"‹the throat then it is identified as having a throat disorder, whereas if the percentage of white is less than 38% then it is identified as not having a throat disorder. The detection program created provides an accuracy of 87.5% on sample data of 8 test data.
The Characteristics of Polyester Concrete with Local Sand of East Borneo as Filter Dewi, Asti Lolita; Tanjung, Rifqi Aulia; Tajalla, Gusti Umindya Nur; Parmita, Ade Wahyu Yusariarta Putra
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.58323

Abstract

Concrete is a mixture of coarse aggregate and fine aggregate mixed with water and cement as a binder and filler. The disadvantages of traditional concrete are that high water absorption causes low chemical resistance, low modulus of elasticity, low impact strength and a long hardening time to reach its maximum properties, namely 28 days. The solution to these shortcomings that is being developed for construction material applications is by using polymers as polymer concrete. In this research, polyester resin and sand aggregate were used as basic materials. Polyester resin is a type of thermosetting polymer that is widely used in various applications such as automotive parts, composites and construction because of its suitable processing characteristics and affordable price. Meanwhile, the sand used is local Kalimantan sand, where from the XRF and XRD test results, local Kalimantan sand is included in the silica sand type. This research varies the weight fraction of polyester resin used to determine its effect on polymer concrete characteristics such as porosity, water absorption, compressive strength, and macro observations. Variations in the polymer weight fraction used were 20%, 25% and 30%. Compressive strength testing was carried out at the age of 7 days of concrete. The results of the porosity test show that the average porosity of all variations is ± 0.5%. Meanwhile, the average value of water absorption for all fractions is 0.2%. And the highest average value of compressive strength in the 30% polyester resin weight fraction was 66.9 MPa. So it can be concluded that all variations meet SNI standards to become concrete materials.
Evaluation of the Validity of Air Kerma Reference Data for Calibration of Radiation Measuring Instruments Zain, Nuril Jannah; Winarno; Astuti, Suryani Dyah; Suhariningsih; Destiani, Reza
Indonesian Applied Physics Letters Vol. 6 No. 1 (2025): Volume 6 No. 1 – December 2025
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v6i1.84055

Abstract

The calibration of radiation measuring instruments at the Health Facility Security Agency (BPFK) Surabaya requires accurate air kerma reference data to ensure the safety and radiation protection of workers. This study aims to validate the air kerma reference data obtained from radioactive decay calculations and direct measurements using standard measuring instruments. Air kerma reference data were obtained through two methods: direct measurement using standard measuring instruments and calculations using the radioactive decay formula. Measurements were conducted with various absorbers (1/10, 1/100, 1/1000) and without absorbers. The results showed that the air kerma values from direct measurements had low standard deviations, indicating consistent results. However, there was a significant relative deviation between the direct measurement data and the decay calculation data for absorbers 1/100 and 1/1000, exceeding the allowable deviation limit of ±20%. This deviation is caused by the ideal conditions assumed in the decay formula, which do not account for external factors such as temperature, pressure, and humidity. Therefore, the air kerma reference data from decay calculations for these absorber variations are not valid for use as calibration references. The proposed solution includes improving the decay formula by incorporating environmental and absorber correction factors, as well as regularly calibrating and verifying the measuring instruments.
The Role of Calcination Temperature Variation in The Sol–Gel Synthesis of Hydroxyapatite Siswanto; Hikmawati, Dyah; Falentina, Winda Dwi
Indonesian Applied Physics Letters Vol. 6 No. 1 (2025): Volume 6 No. 1 – December 2025
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v6i1.84056

Abstract

This study aims to synthesize hydroxyapatite using the sol–gel method with variations in calcination temperature. The hydroxyapatite precursor was derived from eggshell. The egg shell powder was milled using High Energy Milling (HEM) for 20 hours, producing particles measuring 54.84 nm based on Particle Size Analyzer (PSA) results. A 1.67 M calcium dioxide solution obtained from the coral powder was reacted with a 1 M phosphoric acid solution through the sol–gel process. The resulting gel was dehydrated at 110 °C and then calcined at temperatures ranging from 450 to 900 °C for 5 hours. The synthesized products were characterized using X-ray Diffraction (XRD). The results indicated that calcination at 550 °C for 5 hours produced the most stable hydroxyapatite phase, with a volume fraction of 90.8%, a crystallinity degree of 39.8%, and a crystal size of 32.09 nm.
The Innovation of 3D Printing Application in The Making of Bone Scaffold as Spinal Tuberculosis Drug Delivery System Wardhani, Inten Firdhausi; Hikmawati, Dyah; Putra, Alfian Pramudita; Aminatun; Parastuti, Frazna
Indonesian Applied Physics Letters Vol. 6 No. 1 (2025): Volume 6 No. 1 – December 2025
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v6i1.84057

Abstract

The third highest number of tuberculosis (TB) cases was found in Indonesia. In severe cases, there is a chance for this disease to happen in the spine, which is known as spinal tuberculosis. This study examined an innovation that combined 3D-printed bone scaffolds with an injectable bone substitute (IBS) in paste form. Five pore-size variations of the bone scaffolds (600, 800, 1000, 1200, and 1400) µm were printed using an FDM 3D printer and based on Polylactide Acid (PLA) filaments. Moreover, the IBS paste was produced based on nano-hydroxyapatite (nano-HA), gelatin, hydroxypropyl methylcellulose (HPMC), and streptomycin (TB drug). The FTIR test indicates some functional groups were recorded and identified as typical bonds owned by each constituent material: stretching C-H for PLA, PO43- which represented nano-HA, amine for gelatin, stretching C-OH for HPMC, and ether for streptomycin. Furthermore, various pore-size 3D-printed bone scaffolds were characterized by their porosity, resulting in a range of 55.860% to 68.017%. The result of SEM revealed that the IBS-associated scaffold still had micropores on the surface of the scaffold. These pores let the drug load in the IBS paste release, which could be proven by drug release and the anti-TB test. Moreover, this combined biomaterial was confirmed to be a non-toxic, biodegradable material. The innovation of IBS-associated 3D-printed bone scaffold for future treatment of spinal TB represents a potential breakthrough in the medical field. This technology enables localized and regulated drug delivery, reduces systemic adverse effects, and accelerates recovery. Islam considers health as part of hifdz an-nafs (protection of life), one of the primary objectives of maqasid al-shari’ah (Islamic teachings). This development underlined that such innovations are not only scientifically significant but also carry substantial shari (Islamic legal) legitimacy.
Deep Physics-Informed Neural Network (D-PINN) for Real-Time Dynamic Electrical Impedance Tomography (EIT) Reconstruction with Geometrical Uncertainty Robustness Soelistiono, Soegianto
Indonesian Applied Physics Letters Vol. 6 No. 1 (2025): Volume 6 No. 1 – December 2025
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v6i1.84060

Abstract

Electrical Impedance Tomography (EIT) is a vital non-invasive imaging technique for dynamic monitoring, such as lung ventilation. The primary challenge in EIT lies in the inverse problem, which is non-linear, ill-posed, and computationally slow, especially when high accuracy and real-time speed are simultaneously required. Conventional EIT reconstruction algorithms often yield blurred images and are highly susceptible to measurement noise and geometrical uncertainties, such as variations in electrode placement and unknown boundary shapes. This research proposes the Deep Physics-Informed Neural Network (D-PINN), an extended deep learning framework, to achieve accurate and real-time dynamic EIT reconstruction. Unlike purely data-driven methods, our D-PINN integrates the governing Laplace’s Equation directly into the network’s loss function, providing a strong physical constraint to significantly enhance image quality. The innovative focus of this study is addressing the critical gap in model uncertainty robustness. We develop a stochastic D-PINN training scheme that not only solves the conventional inverse problem (predicting conductivity) but also simultaneously accounts for small variations in boundary geometry or electrode positions. Initial simulation results are expected to show that D-PINN consistently:1. Reduces the reconstruction inference time to the millisecond scale, enabling true real-time monitoring. 2. Significantly improves the spatial resolution and image contrast (measured by the Structural Similarity Index / SSIM) compared to standard iterative methods. 3. Maintains high accuracy even when the input measurement data is noisy and the assumed forward geometrical model is intentionally perturbed, which is crucial for real-world instrumentation applications. This work is expected to advance EIT into a more reliable and robust real-time imaging tool.
DEVELOPMENT OF A HEMOGLOBIN LEVEL PREDICTION MODEL BASED ON PHOTOPLETHYSMOGRAPH DATA USING EXTREME GRADIENT BOOSTING Arisgraha, Franky Chandra Satria; Ama, Fadli; Kusumo, Wirotomo Bayunoto Prono
Indonesian Applied Physics Letters Vol. 6 No. 1 (2025): Volume 6 No. 1 – December 2025
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v6i1.84086

Abstract

Anemia is a growing global health concern, driving the need for non-invasive detection methods. This research develops a non-invasive hemoglobin (Hb) level prediction model utilizing Photoplethysmography (PPG) signals and the Extreme Gradient Boosting (XGBoost) algorithm, addressing the limitations of conventional invasive and time-consuming approaches. PPG signals, captured by optical sensors (red 660 nm and infrared 880 nm) on the fingertip, monitor blood volume changes that correlate with Hb levels based on the Beer-Lambert Law. Following pre-processing of secondary data from 68 subjects (including missing value handling and gender encoding) and average Systolic Peak feature extraction, the XGBoost model was trained and evaluated. To enhance performance and overcome data limitations, data augmentation was implemented, expanding the sample to 204. Evaluation results demonstrate significant improvement: on the original data, the model achieved an MAE 0,0769, RMSE 0,1117, and R² 0,4954. For the post-augmentation, performance drastically improved to an MAE 0,0190, RMSE 0,0254, and the R² of 0,9724. This increased R² indicates the model's ability to capture 97,24%; of hemoglobin variability, while reduced MAE and RMSE signify higher prediction accuracy and better generalization, making this model reliable for non-invasive Hb prescreening and potentially supporting anemia diagnosis.

Page 5 of 5 | Total Record : 50

 1   2   3   4   5 

Filter by Year

2020 2025


Reset
Filter By Issues
All Issue Vol. 6 No. 1 (2025): Volume 6 No. 1 – December 2025 Vol. 5 No. 1 (2024): June 2024 Vol. 4 No. 2 (2023): December Vol. 4 No. 1 (2023): June Vol. 3 No. 2 (2022): December Vol. 3 No. 1 (2022): June Vol. 2 No. 2 (2021): December Vol. 2 No. 1 (2021): June Vol. 1 No. 2 (2020): Desember Vol. 1 No. 1 (2020): June