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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 3,452 Documents
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SYNDIAG: an expert system for disease syndrome diagnosis of traditional Vietnamese medicine Truong Hong Thuy; Ha Manh Toan; Vu Tung Lam; Nguyen Hoang Phuong
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 5: October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i5.25831

Abstract

Vietnam medicine consists of traditional Vietnam medicine and Western medicine. There is a lack of experienced traditional medicine practitioners, therefore, it needs to develop an expert system supporting medical practitioners in diagnosis. In this paper, we present an overview of syndrome diagnosis (SYNDIAG), a rule-based expert system for disease syndrome diagnosis in traditional Vietnamese medicine. The system consists of five components: knowledge base, inference engine, knowledge acquisition, explanation, and user interface. The paper focuses on how the rule base is constructed, managed, and used. At present, this knowledge base contains more than 1,000 rules used for the diagnosis of 50 disease syndromes of traditional Vietnamese medicine. The inference engine of the system applies the knowledge propagation and the algebra structure of MYCIN-like systems. We also present here the first evaluation of SYNDIAG by the practitioners of traditional medicine, who have been playing a very important role by providing the system with their knowledge.
A novel Ethernet based processing system for remote source harmonic detection Mazin R. Khalil; Laith A. Mohammed; Omar N. Yousif
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24091

Abstract

This work is carried out to objectively establish a new method to detect harmonics and measure the total harmonic distortion (THD) in a remote source, such as a high voltage transformer. The proposed approach utilized embedded design techniques to construct an embedded processor system with Ethernet intellectual property core to acquire data from a remote harmonics source. The designed system has several notable merits, namely, it is portable that can be applied in the work field, and it avoids workers from being subject to a hazard high voltage shock as well as its simplicity and high accuracy. The harmonics detection and analysis are achieved by inserting a microcontroller system near the high voltage transformer to acquire the necessary data and transmit it to a remote embedded processor system that is used to detect and analyze the harmonics. The microcontroller and the processor systems are connected by a wide-area network (WAN) through Ethernet and transmission control protocol/internet protocol (TCP/IP) protocols. The processor system is accommodated to perform 128 points fast Fourier transform for harmonics detection. Matlab simulations are used to validate the results. It is found that the results match very accurately the simulation results with an error of less than 0.02%.
Deep learning-based image super-resolution using generative adversarial networks with adaptive loss functions Hani Q. R. Al-Zoubi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 4: August 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i4.26105

Abstract

This study investigates deep learning based single image super-resolution (SISR) and highlights its revolutionary potential. It emphasizes the significance of SISR, and the transition from interpolation to deep learning driven reconstruction techniques. Generative adversarial network (GAN)- based models, including super-resolution generative adversarial network (SRGAN), video super-resolution network (VSRResNet), and residual channel attention-generative adversarial network (RCA-GAN) are utilised. The proposed technique describes the loss functions of the SISR models. However, it should be noted that the conventional methods frequently fail to recover lost high-frequency details, which signify their limitations. The current visual inspections indicate that the suggested model can perform better than the others in terms of quantitative metrics and perceptual quality. The quantitative results indicate that the utilised model can achieve an average peak signal-to-noise ratio (PSNR) enhancement of X dB and an average structural similarity index (SSIM) increase of Y. A range of improvements of 7.12-23.21% and 2.75-10.00% are obtained for PSNR and SSIM, respectively. Also, the architecture deploys a total of 2,005,571 parameters, with 2,001,475 of these being trainable. These results highlight the model’s efficacy in maintaining key structures and generating visually appealing outputs, supporting its potential implications in fields demanding high-resolution imagery, such as medical imaging and satellite imagery.
Low-cost and open-source anthropomorphic prosthetics hand using linear actuators Triwiyanto Triwiyanto; I Putu Alit Pawana; Torib Hamzah; Sari Luthfiyah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14799

Abstract

A robust, low cost, open-source, and low power consumption in the research of prosthetics hand is essential. The purpose of this study is to develop a low-cost, open-source anthropomorphic prosthetics hand using linear actuator based on electromyography (EMG) signal control. The main advantages of this proposed method are the low-cost, lightweight and simplicity of controlling the prosthetic hand using only single channel. This is achieved by evaluating the DC motor and exploring number of locations of the EMG signal. The development of prosthetics hand consists of 3D anthropomorphic hand design, active electrodes, microcontroller, and linear actuator. The active electrodes recorded the EMG signal from extensor carpi radialis longus. The built-in EMG amplifier on the electrode amplified the EMG signal. Further, the A/D converter in the Arduino microcontroller converted the analog signal into digital. A filtering process consisted of bandpass and notch filter was performed before it used as a control signal. The linear actuator controlled each finger for flexion and extension motion. In the assessment of the design, the prosthetic hand capable of grasping ten objects. In this study, the cost and weight of the prosthetics hand are 471.99 US$ and 0.531 kg, respectively. This study has demonstrated the design of low cost and open-source of prosthetics hand with reasonable cost and lightweight. Furthermore, this development could be applied to amputee subjects.
Two new classes of conjugate gradient method based on logistic mapping Banaz Hamza Jahwar; Alaa Luqman ibrahim; Sherzad Muhammed Ajeel; Salah Gazi Shareef
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 1: February 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i1.25264

Abstract

Following the standard methods proposed by Polak-Ribiere-Polyak (P-R), in this work we introduce two new non-linear conjugate gradient methods for solving unconstraint optimization problem, our new methods based on P-R. Standard method (P-R) have performance well in numerical result but does not satisfy global convergency condition. In this paper we modified double attractive and powerful parameters that have better performance and good numerical result than P-R method, also each of our robust method can satisfies the descent condition and global convergency condition by using wolf condition. More over the second method modified by logistic mapping form, the main novelty is their numerical results and demonstrate performance well with compare to a standard method.
EdgeShield: a robust and agile cybersecurity architecture for the internet of medical things Anass Misbah; Anass Sebba; Imad Hafidi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 4: August 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i4.26989

Abstract

We present EdgeShield, a lightweight pipeline that streamlines internet of medical things (IoMT) traffic analysis by pairing aggressive dimensionality-reduction with federated model aggregation. It employs systematic preprocessing, advanced feature selection, and robust sampling to reduce computational overhead while enhancing performance. Through feature engineering techniques such as principal component analysis (PCA), targeted feature selection, and embedding methods, EdgeShield reduces dataset dimensionality by 96%, enabling near real-time detection and prevention of cyber attacks on resource-constrained edge devices. To harden the IoMT perimeter, EdgeShield trains ten lightweight edge models in just 54s and merges their parameters into a single global clas sifier with negligible extra delay. This method requires no additional training or predictions, thus accelerating deployment. Additionally, by using a compact dataset with five top-performing features and PCA with two components, EdgeShield consistently achieves accuracy levels exceeding 99.2% for individual edge models and the consolidated global model. With a built-in continuous improvement loop, EdgeShield dynamically adapts to emerging data patterns and operational conditions, driving substantial advancements in IoMT ecosystem management. This approach delivers both rapid machine learning model deployment and robust cyber attack detection, illustrating its potential to revolutionize IoMT security and elevate healthcare data integrity.
Indoor positioning system using BLE beacon to improve knowledge about museum visitors Andreas Handojo; Tanti Octavia; Resmana Lim; Jonathan Kurnia Anggita
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14886

Abstract

Generally, a museum has many locations and artifacts collection that display for visitors. Museum manager often have difficulty in obtaining information on visitors behavior such as, is there are particular locations/artifacts in the museum that are frequently/rarely visit by museum visitors, how long visitors spend their time in particular locations/artifacts, etc. The purpose of this study is try to build a suitable system in order to improve knowledge about the behavior of museum visitors by identifying the position of visitors in the museum. This study uses Bluetooth Low Energy (BLE) Beacon that place around the museum. The visitor mobile phone will detect BLE beacon signal, then the mobile phone application will calculated the visitor’s mobile phone position using the signal strength from the BLE beacons that are detected. The application then sends it to the computer server to display it in as museum visitor heat map. From this information, the museum manager could find out the visitors behavior movement and know which areas/artifacts that frequently/rarely visit by museum visitors. According to distance error testing which compare real location and position of the calculation, it is show that the average of distance error is around 140 cm. So, it can be concluded that the information obtained is sufficient enough to represent the position of museum visitors.
RF-DC conversion for RF energy harvesting from digital TV signals using voltage multiplier circuits Piyapat Panmuang; Amornthep Sonsilphong; Chaiyong Soemphol
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 2: April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i2.25593

Abstract

Due to the development of wireless communications, there has been a growth in the use of IoT devices and sensor nodes. A potential power source for powering equipment in remote or inaccessible locations is necessary. This research investigates the feasibility of employing digital television (DTV) signals as an energy harvesting system, with a focus on RF-DC conversion using a voltage multiplier circuit. Commercial 5 and 9 element yagi-uda antennas are used as receiver for ambient DTV signal. The device’s performance is initially evaluated within the laboratory setting, it has been shown that when the RF signal generator is at 660 MHz, the proposed energy harvesting device can generate a maximum DC voltage of 781.3 mV and 1056.4 mV for 5 and 9 element antenna, respectively. This is based on measurement of voltage output when using the input signal from DTV base stations in Thailand. It was found that the voltage output levels decreased gradually with increasing distance ranging from 153.4 V at 0.1 km to 4.5 mV at 10 km for 5 element yagi-uda antenna. In contrast, the 9-element yagi-uda antenna consistently exhibited higher voltage levels, ranging from 354.7 mV at 0.1 km to 12.6 mV at 10 km.
Performance enhancement of PV generator using a sensor based dual axis solar tracking system in Algeria Sakina Atoui; Harb Hadjer; Belaïd Abdelghani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 6: December 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i6.26872

Abstract

This article presents the implementation of a two-axis solar tracking system and its impacts to increase the performance of the photovoltaic system in northern Algeria. The system enhances the efficiency of solar systems by optimizing their exposure to sunlight making the sunbeam perpendicular to solar panel. The main objective of the study is to develop a technically proficient and economically viable solution to increase solar energy production. The design relies on integrating light sensors and motors controlled by an Arduino board, enabling automatic adjustment of solar panel positions. This approach offers dynamic and precise orientation, based on light dependent resistor (LDR) sensor design and threshold value, resulting in a significant increase in energy output. The results show that the dual-axis solar tracking system can capture 60.64% more solar energy, taking into account the power consumption of the two electric actuators. The findings of this study will positively influence the promotion of clean and sustainable energy sources while providing a practical solution for more efficient utilization of solar energy in Algeria.
A method for semantic-based image retrieval using hierarchical clustering tree and graph Nguyen Minh Hai; Thanh The Van; Tran Van Lang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 5: October 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i5.24086

Abstract

Semantic extraction for images is an urgent problem and is applied in many different semantic retrieval systems. In this paper, a semantic-based image retrieval (SBIR) system is proposed based on the combination of growth partitioning tree (GP-Tree), which was built in the authors’ previous work, with a self-organizing map (SOM) network and neighbor graph (called SgGP-Tree) to improve accuracy. For each query image, a similar set of images is retrieved on the SgGP-Tree, and a set of visual words is extracted relying on the classes obtained from mask region-based convolutional neural networks (R-CNN), as the basis for querying semantic of input images on ontology by simple protocol and resource description framework query language (SPARQL) query. The experiment was performed on image datasets, such as ImageCLEF and MS-COCO, with precision values of 0.898453 and 0.875467, respectively. These results are compared with related works on the same image dataset, showing the effectiveness of the methods proposed.

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