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Jurnal Elektronika dan Telekomunikasi
Published by Lembaga Ilmu Pengetahuan Indonesia
ISSN : 14118289     EISSN : 25279955     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering Engineering
Jurnal Elektronika dan Telekomunikasi (JET) is an open access, a peer-reviewed journal published by Research Center for Electronics and Telecommunication - Indonesian Institute of Sciences. We publish original research papers, review articles and case studies on the latest research and developments in the field of electronics, telecommunications, and microelectronics engineering. JET is published twice a year and uses double-blind peer review. It was first published in 2001.
Arjuna Subject : -
Articles 470 Documents
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Implementation of Internet of Things-Based Autofeeder to Maintain Koi Pond Water Quality Helmy, Helmy; Pernanda, Suko Tyas; Nursaputro, Septiantar Tebe; Pratiwi, Mona Inayah; Rahmaditya, Brian; Anggreini, Clara Silvia
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.717

Abstract

Koi fish farming requires careful monitoring of water temperature and pH to prevent adverse impacts on the fish. This study presents a prototype IoT-based autofeeder that integrates real-time water quality monitoring and automatic feeding, controllable via both an Android application and local device buttons. The system allows users to configure feeding schedules, feed throw levels, and durations, as well as set pH thresholds. When the pH exceeds the safe range, the system automatically stops feeding and sends notifications, enabling the user to inspect and maintain pond water quality. The findings demonstrate that the dispensing level significantly influences the feed-throwing distance; higher dispensing levels result in longer distances. Small-sized feed (S) consistently produced the highest output, followed by medium-sized (M) and large-sized (L). Increasing the feeding duration enhanced the weight of the released feed. Additionally, the average delay in sensor data transmission to the database was recorded at 5.48 seconds. The data loss rate during the testing period was 1.72%, which is considered acceptable and does not adversely affect system operations. The data transmission system demonstrated good and stable performance with relatively low data loss.
Phase-Sensitive Radar Using ADALM-Pluto SDR and Cantenna for Sub-Millimeter Displacement Measurement Mozef, Eril; Rasyid, Ridho Shofwan; Sulaeman, Enceng; Mulyana, Tiyo Rizky; Al Farik, Fahrizal; Junjunan, Thaskia Qolbi
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.757

Abstract

The capability of phase-sensitive radar to detect sub-millimeter displacement has been widely demonstrated, enabling a range of applications such as structural vibration monitoring, human vital-sign detection, gesture sensing, and precision motion tracking. In these domains, particularly in non-contact human respiratory monitoring, conventional phase-sensitive radar systems offer key advantages, including high phase stability, robust performance under non-ideal lighting or environmental conditions, and the ability to operate without physical contact. These strengths make them effective for capturing small periodic chest movements required for accurate respiratory assessment. However, conventional hardware implementations often suffer from limited flexibility, higher development cost, and increased design complexity. These constraints motivate the shift toward software-defined radio (SDR) solutions, which provide reconfigurability, simplified prototyping, and significantly lower cost while retaining the essential phase-sensitive capabilities. This motivation forms the basis of the present research. This study realizes a phase-sensitive radar using an ADALM-Pluto SDR operating at 2.45 GHz with a cantenna antenna configuration. Compared with previous SDR-based works that focus primarily on Doppler vital-sign extraction or require more elaborate RF front-ends, the proposed system emphasizes displacement-resolution enhancement through careful phase processing while maintaining minimal hardware complexity. The combination of a compact SDR platform, simple antenna structure, and optimized signal processing pipeline yields a practical and accessible radar prototype. Experimental results demonstrate that the proposed system achieves a displacement resolution of 0.5 mm, meeting the requirements for developing a reliable respiratory-monitoring application and confirming the suitability of SDR-based phase-sensitive radar for low-cost biomedical sensing.
Front Cover Vol. 25 No. 2 Prini, Salita Ulitia
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.833

Abstract

Feature Selection and Class Imbalance Machine Learning for Early Detection of Thyroid Cancer Recurrence: A Performance-Based Analysis Wantoro, Agus; Caesarendra, Wahyu; Syarif, Admi; Soetanto, Hari
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.758

Abstract

Early detection of thyroid cancer recurrence is a crucial factor in patient survival and treatment effectiveness. Misdetection results in disease severity, high cost, recovery time, and decreased service quality. In addition, the main challenges in developing a Machine Learning (ML)-based detection decision support system are class imbalance in medical data and high feature dimensions that can affect model accuracy and efficiency. This study proposes a feature selection-based approach and class imbalance handling to improve the performance of early detection of Thyroid cancer. Several feature selection techniques, such as Information Gain (IG), Gain Ratio (GR), Gini Decrease (GD), and Chi-Square (CS), can select features based on weighted ranking. In addition, to overcome the imbalanced class distribution, we use the Synthetic Minority Over-Sampling Technique (SMOTE). ML classification models such as k-NN, Tree, SVM, Naive Bayes, AdaBoost, Neural Network (NN), and Logistic Regression (LR) are tested and evaluated based on a confusion matrix, including accuracy, precision, recall, time, and log loss. Experimental results show that the combination of imbalanced class handling strategies significantly improves the prediction performance of ML algorithms. In addition, we found that the combination of CS+NN feature selection techniques consistently showed optimal performance. This study emphasizes the importance of data pre-processing and proper algorithm selection in the development of a machine learning-based thyroid cancer detection system.
Comparative Analysis and Mitigation of Extremely Low Frequency (ELF) Magnetic Field Exposure from Smartphone Internal Yudha, Bayu Wira; Zakaria, Hasballah
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.781

Abstract

While public concern regarding smartphone electromagnetic field (EMF) exposure is largely focused on radio frequency (RF) emissions, this study investigates the overlooked extremely low frequency (ELF) magnetic fields originating from internal hardware circuits, such as the Power Management Integrated Circuit (PMIC). This research employs a quantitative experimental methodology to characterize and compare the near-field emissions of two smartphone models with distinct internal architectures: the Xiaomi Redmi Note 8 Pro (12nm mid-range chipset) and the Samsung Galaxy S23 (4nm premium chipset). Magnetic field intensity measurements were conducted using a Hall-effect Gaussmeter, both in free space and with a 3D-printed cubic head phantom fabricated from PETG and filled with a conductive saline-based tissue-simulating liquid (TSL). The primary findings reveal unique ELF emission "fingerprints," where the premium-engineered device exhibits a peak exposure of 0.269 mT—nearly three times lower than its mid-range counterpart at 0.799 mT. Theoretical analysis utilizing the Biot-Savart Law attributes this reduction to the minimized current loop areas inherent in advanced 4nm process nodes compared to older 12nm architectures. Quantitative analysis of mitigation strategies demonstrates that spatial separation (a 15 cm distance) is the most dominant factor, achieving up to 90.7% attenuation, which surpasses the material shielding provided by the phantom (82.0%). Although peak contact exposure can exceed the ICNIRP reference level, the rapid near-field decay ensures compliance at minimal practical distances. This study concludes that ELF exposure is a function of engineering quality rather than network technology, and mitigation is most effectively achieved through physical distance.
Preface Vol. 25 No. 2 Prini, Salita Ulitia
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.834

Abstract

Fabrication of Quartz Crystal Microbalance Coated with GO/PVC Nanofiber for Benzene Detection as Tuberculosis Biomarker Nugroho, Doni Bowo; Kamal, Nada Nadzira Ayasha; Wati, Rosita; Resfita, Nova
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.765

Abstract

Tuberculosis (TB) is a highly contagious illness and a major contributor to global mortality, with over 1.5 million deaths reported annually. TB is caused by Mycobacterium tuberculosis (Mtb), which is often difficult to diagnose in the early stages of infection. Existing diagnostic methods are limited by long processing times, high costs, and suboptimal sensitivity. Therefore, this study aimed to develop a Quartz Crystal Microbalance (QCM)-based biosensor employing polyvinyl chloride (PVC) nanofibers coated with graphene oxide (GO) for rapid detection of volatile TB biomarkers, particularly benzene. The sensing platform utilized a 10 MHz AT-cut silver electrode QCM coated with electrospun PVC nanofibers, followed by GO deposition via immersion. Scanning Electron Microscopy (SEM) showed uniform nanofibers with diameters increasing from 183 ± 54 nm to 348 ± 50 nm after GO coating, while FTIR confirmed the presence of GO functional groups. Sensor evaluation revealed a clear and concentration-dependent frequency shift, with a sensitivity of 1.88 Hz·L/mg, a strong linear correlation (R² = 0.99) across 1.18–23.68 mg/L, and a fast response time of 71 seconds. The limits of detection and quantification were determined to be 0.88 mg/L and 2.66 mg/L, respectively. Adsorption followed the Langmuir isotherm model, indicating monolayer uptake. These results demonstrate that the GO/PVC nanofiber-coated QCM offers a promising, low-cost, and sensitive approach for TB biomarker detection in breath analysis.
PID Controller-Based Closed-Loop Fast Charging of Lithium-Ion Batteries Using the CCCV Method Sutikno, Tole; Wahono, Tri; Baswara, Ahmad Raditya Cahya
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.749

Abstract

This paper presents a closed-loop fast charging system for lithium-ion batteries based on the Constant-CurrentConstant-Voltage (CCCV) method enhanced with a ProportionalIntegralDerivative (PID) controller. The proposed system dynamically regulates the charging parameters by using real-time feedback from voltage and current sensors, with the aim of improving the efficiency of the charging and ensuring battery safety. Experimental results demonstrate that the PID-controlled method maintains a higher current during the initial bulk charging phase, significantly reduces total charging time, and avoids harmful voltage overshoot. Compared to conventional CCCV charging, the system achieves more stable voltage regulation and gradual current tapering, effectively minimizing thermal stress and preventing overcharging. A comparative analysis shows that the PID approach outperforms traditional methods in terms of energy efficiency, thermal management, and operational safety. The system architecture is suitable for integration into Battery Management Systems (BMS) of electric vehicles, portable electronics, and renewable energy storage. This research not only validates the practicality of using PID in fast charging applications but also lays the foundation for future enhancements using intelligent control strategies and adaptive learning algorithms. The findings suggest that PID-controlled charging systems offer a promising solution to the challenges of rapid, reliable, and safe energy replenishment in modern battery-powered technologies.
Back Cover Vol. 25 No. 2 Prini, Salita Ulitia
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.836

Abstract

Smartphone-Based Colorimetric Platform with RGB-CIELAB Multivariate Regression and 3D-Printed Illumination for Portable Multi-Analyte Detection Manurung, Robeth Viktoria; Telaumbanua, Jonathan Edwards; Lim, Richard Anthony; Astuti, Winda; Mada, Dedi; Andreani, Agustina Sus
Jurnal Elektronika dan Telekomunikasi Vol 25, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.798

Abstract

Smartphone-based colorimetry has become a promising alternative to bulky and expensive spectrophotometers for portable and field analysis. This study aims to develop Colorizer, a modular smartphone-based colorimetric platform that provides accurate and affordable measurements for environmental, chemical, and biomedical applications. The system combines a custom Android app with a 3D-printed sampling station featuring controlled LED illumination, RGB-to-CIELAB conversion, calibration blanking, and multivariate regression modeling to ensure consistent measurements across devices. Illumination is controlled by an ESP32 microcontroller and activated via Bluetooth inside a light-tight chamber to minimize ambient interference. Validation experiments with synthetic dye assays showed strong agreement for red and yellow standards (R² = 0.944 and 0.940, RMSE = 6.503 and 6.955) and lower accuracy for blue assays (R² = 0.868, RMSE = 10.423), likely due to reduced signal-to-noise ratio at higher absorbance. These findings confirm that the platform delivers reliable and portable performance while functioning fully offline with locally stored calibration data. The study suggests that Colorizer offers a practical, low-cost alternative to benchtop spectrophotometers, with future work to validate its use with real-world analytes such as water contaminants, food safety markers, and clinical biomarkers.

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