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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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Bacterial Classification Using Deep Structured Convolutional Neural Network for Low Resource Data M Faizal Amri; Asri Rizki Yuliani; Dwi Esti Kusumandari; Artha Ivonita Simbolon; M. Ilham Rizqyawan; Ulfah Nadiya
Jurnal Elektronika dan Telekomunikasi Vol 23, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.533

Abstract

Bacterial identification is an essential task in medical disciplines and food hygiene. The characteristics of bacteria can be examined under a microscope using culture techniques. However, traditional clinical laboratory culture methods require considerable work, primarily physical and manual effort. An automated process using deep learning technology has been widely used for increasing accuracy and decreasing working costs. In this paper, our research evaluates different types of existing deep CNN models for bacterial contamination classification when low-resource data are used. They are baseline CNN, GCNN, ResNet, and VGGNet. The performance of CNN models was also compared with the traditional machine learning method, including SIFT+SVM. The performance of the DIBaS dataset and our own collected dataset have been evaluated. The results show that VGGNet achieves the highest accuracy. In addition, data augmentation was performed to inflate the dataset. After fitting the model with augmented data, the results show that the accuracy increases significantly. This improvement is consistent in all models and both datasets.
Appendix Vol. 23 No. 1 Salita Ulitia Prini
Jurnal Elektronika dan Telekomunikasi Vol 23, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Oxygen Level System Development in WSN and IoT-Based Factory Rifki Muhendra; Aisyah Amin
Jurnal Elektronika dan Telekomunikasi Vol 23, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.512

Abstract

The health of workers is essential to factory productivity. The lack of oxygen experienced by factory workers for a prolonged duration can disrupt the brain system. One solution to this problem is to build manufacturing facilities with well-maintained airflow, especially oxygen. The system can flow air from outside the factory into the factory based on the measurement of the oxygen level. In this research, an airflow system using the internet of things (IoT) and wireless sensor network (WSN) technology was developed to ensure no oxygen shortage in the factory space. The system comprises three main parts: an oxygen level sensor, a fan controller circuit, and a cloud-based communication system. The oxygen level sensor can measure the volume of oxygen in the factory room and is also connected to the fan controller to control the airflow to the radio-frequency (RF) communication factory room. Oxygen level monitoring data are also sent to the cloud server so that the condition of the factory space can be monitored remotely using internet computers and mobile devices. Performance tests that have been carried out show that the system can increase the oxygen level by 82% from its pre-installed condition. The system built is easy-to-install, low-power, and reliable, with a data loss value of only 1.67%. WSN implementation at the factory does not require a lot of wiring, thus making the system cheaper.
Two-Stage Object Detection for Autonomous Vehicles With VGG-16 Based Faster R-CNN Dewi, Arnetta Listiana; Pardede, Hilman F.; Suryawati, Endang; Pratiwi, Hasih; Heryana, Ana; Yuliani, Asri R; Ramdan, Ade
Jurnal Elektronika dan Telekomunikasi Vol 24, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.551

Abstract

The implementation of object detection for autonomous vehicles is essential as it is necessary to identify common object on the street so proper response could be designed. While single stage object may be smaller in computations, two-stage object detection is preferred due to the ability to localize the object. In this paper, we propose to use Faster R-CNN with VGG-16 backbone for detections of object on the street. We evaluate the method with open image subset by selecting objects that are common on street. We explore several hyper-parameters setup such as learning rate and the number of ROI regions to find the optimum set-up. We found that the use of learning rate 10-6 with Adam optimizer to be the optimum value for this task. We also found that increasing the number of ROI may benefit the performance. This shows that there is potential for getting a higher mAP with increase the amount of RoI.
Design of Brushless DC Motor Driver Based on Bootstrap Circuit Fathoni, Khoirudin; Apriaskar, Esa; Salim, Nur Azis; Sulistyawan, Vera Noviana; Satria, Rifki Lukman; Hidayat, Syahroni
Jurnal Elektronika dan Telekomunikasi Vol 23, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.563

Abstract

Brushless DC (BLDC) motor is a three-phase motor that cannot work directly with DC current but requires electronic commutation to replace the brush function in DC motor. This paper aims to implement BLDC motor driver integration based on bootstrap circuit using Autodesk Eagle. The driver board consist of bootstrap circuit based on IR2110, MOSFETs, three voltage regulator, ESP32 microcontroller and ACS712 current sensor connection, logic level converter, and BLDC hall effect signal sensor conditioning. The research proposes bootstrap capacitor calculation based on charging/discharging capacitor principle and the minimum motor speed rotation. The implemented driver has 14x10 cm dimension tested to drive 24V/135W/6000rpm sensored BLDC motor using six steps commutation with pulse width modulation (PWM) inserted programmatically in ESP 32 to drive the high side MOSFET of the driver without AND gate circuit. The effect of pwm frequency and dutycycle variation to the speed and current of the motor is investigated. The results showed that the driver with both 12 V and 24 V voltage source and 68 μF bootstrap capacitor work optimally in 20 KHz PWM frequency both in open loop and closed loop speed control test. The motor reach 129 W for the largest power and 5250 rpm for the fastest speed in 24 V supply.
Computational Analysis of Electrical Impedance Spectroscopy for Margin Tissue Detection in Laparoscopic Liver Resection Sulistia, Sulistia; Riyanto, Riyanto; Busono, Pratondo; Kurniawan, Affandi Faisal; Saefan, Joko; Kurniawan, Wawan; Baidillah, Marlin Ramadhan
Jurnal Elektronika dan Telekomunikasi Vol 24, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.630

Abstract

Margin tissue detection during intraoperative laparoscopic liver resection (LLR) is required to prevent tumor recurrence and reduce the likelihood of further surgery. This study proposes an electrical impedance spectroscopy (EIS) method for margin tissue detection in LLR to determine the boundary interface of normal and cancerous tissue. The proposed method of this study has three objectives: (1) designing the electrode array configuration to collect multiple EIS impedance measurements, (2) implementing the Feedforward Neural Network (FNN) to classify the orientation of margin tissue relative to the electrode array by using time-difference impedance indexes, and (4) governing the inflection point method based on impedance indexes to detect the margin tissue location. The proposed method is evaluated by a 3D numerical simulation of liver tissue composed of cancerous lumps with Iac = 1 mA alternating injection current  at frequencies: lf = 1 kHz and hf = 100 kHz. The electrode array is composed of 16 electrode pairs each for injection current and voltage measurements. The variation of margin tissue orientation relative to the electrode array direction was considered to occur in unidirectional, perpendicular, and diagonal direction with noise variations (Signal-to-Noise-Ratio: 50 to 90 dB). The FNN trained on 2,400 data points achieves True Positive Rate (TPR) value as 90.2%, 99.4%, and 96.6% for diagonal, perpendicular, and unidirectional respectively in margin tissue orientation classification, while the inflection point method detects margin tissue location with 75% location at the unidirectional orientation (y-axis).
Back Cover Vol. 23 No. 2 Prini, Salita Ulitia
Jurnal Elektronika dan Telekomunikasi Vol 23, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Estimating the Differential Mode Noise of a DC-DC Converter Yoppy, Yoppy; Mandaris, Dwi; Bakti, Aditia Nur; Nugroho, Hutomo Wahyu; Yudhistira, Yudhistira; Hamdani, Deny
Jurnal Elektronika dan Telekomunikasi Vol 23, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.558

Abstract

Electromagnetic noise emission is inevitable in a DC-DC converter due to the employed switching technique. In low frequency, the noise propagating through cabling and conductive media is called a conducted emission. A conducted emission consists of differential mode and common mode noise. It is advantageous to know an estimate of emission level for each mode during the design phase so that suitable mitigation can be included earlier.. This paper aims to focus on a method to estimate the differential mode noise emission of a DC-DC converter. The estimation is computed using the input capacitor complex impedance and the current that flows through it. As a study case, a boost and buck converters are used for evaluation. The estimation and measurement results are compared. Despite differences at some frequencies, the estimated and measured results generally  agree well. Because of its simplicity, the proposed method can be used as a practical tool in the EMC aspect of DC-DC converter design.
Back Cover Vol. 24 No. 1 Prini, Salita Ulitia
Jurnal Elektronika dan Telekomunikasi Vol 24, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.672

Abstract

Nutrition, pH, Temperature, and Humidity Monitoring Hydroponics System based on Android Oktivasari, Prihatin; Pasai, Muda Wali Samudra; Mustofa, Mustofa; Royhan, Royhan; Kurniawan, Asep
Jurnal Elektronika dan Telekomunikasi Vol 24, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.585

Abstract

Agriculture plays a very important role in the lives of Indonesian people. With technological advances and the increasing limitation of agricultural land, the patterns of matching crops in societies have changed. Innovations have been implemented, one of which is the use of technology such as hydroponic systems. One of the main factors that influence the success of hydroponic methods is temperature and humidity. The research aims to design and develop an autonomic control system that uses Fuzzy Logic to regulate the temperature and moisture of hydroponic plants, as well as to design the control of the nutrition and pH supply of hydrogen plants. Hydroponics plant control systems are implemented using microcontrollers and DHT22, TDS sensors, and pH sensors. In addition, an Android-based interface has been developed to monitor and control the system remotely via an internet connection. In this study the accuracy of the TDS sensor is 96.5%, the pH sensor was 98.19%, and the precision of the Fuzzy logic system at temperature and humidity is 100%

Page 41 of 47 | Total Record : 470

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