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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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Sliding mode control of a PMSM railway traction drive fed by multi-level inverter Vo Thanh Ha; Vo Quang Vinh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 6: December 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i6.24369

Abstract

This work offers the sliding mode control (SMC) based control scheme for a railway traction transmission system fed by a five-level T-type inverter. This nonlinear control approach is created for the speed and torque loop control of the permanent magnet synchronous motor (PMSM) railway traction drive system supplied by a multi-level inverter. The article also includes a mathematical model of a PMSM motor and torque load to design controllers. The paper expressed the vector voltage modulation design incorporating a five-level T-Type inverter. The research proposes a control scheme for the railway traction drive system that enhances transmission quality by lowering the torque ripper and stator current harmonic distortion and extending converter life. Through MATLAB simulation, the study findings are validated.
Model development for pneumonia detection from chest radiograph using transfer learning Ojo Abayomi Fagbuagun; Obinna Nwankwo; Samson Adebisi Akinpelu; Olaiya Folorunsho
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 3: June 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i3.23296

Abstract

Accurate interpretation of chest radiographs outcome in epidemiological studies facilitates the process of correctly identifying chest-related or respiratory diseases. Despite the fact that radiological results have been used in the past and is being continuously used for diagnosis of pneumonia and other respiratory diseases, there abounds much variability in the interpretation of chest radiographs. This variability often leads to wrong diagnosis due to the fact that chest diseases often have common symptoms. Moreover, there is no single reliable test that can identify the symptoms of pneumonia. Therefore, this paper presents a standardized approach using convolutional neural network (CNN) and transfer learning technique for identifying pneumonia from chest radiographs that ensure accurate diagnosis and assist physicians in making precise prescriptions for the treatment of pneumonia. A training set consisting of 5,232 optical coherence tomography and chest X-ray images dataset from Mendelev public database was used for this research and the performance evaluation of the model developed on the test set yielded 88.14% accuracy, 90% precision, 85% recall and F1 score of 0.87.
Attributes conducive to anthropomorphism in artificial intelligence Rizwan Syed; Hassan Mistareehi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27483

Abstract

The rapid development of artificial intelligence (AI), particularly large language models (LLMs), has generated both enthusiasm and concern regarding its role in society. While these systems demonstrate impressive technical capabilities, public acceptance is often hindered by perceptions of unpredictability, mistrust, and fears amplified by media narratives. One potential strategy to improve user acceptance is anthropomorphism, the attribution of human-like qualities to AI systems which can make interactions feel more natural and trustworthy. This paper investigates the attributes most conducive to anthropomorphism by conducting a structured review across psychology, human-robot interaction, communication studies, and business applications. The analysis identifies key traits such as emotional expressiveness, conversational coherence, adaptive social behavior, and role-based framing that enhance perceptions of AI as relatable and dependable. By synthesizing these insights, we propose a conceptual framework that highlights the psychological, social, and technical dimensions of anthropomorphism in AI. The findings provide guidance for designing AI systems that balance efficiency with user trust, thereby supporting more effective integration of AI into business, research, and everyday life.
Effective capacity analysis of full-duplex-cooperative non-orthogonal multiple access systems Huu Quy Tran; Samarendra Nath Sur
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.v22i5.25518

Abstract

This study explores a dual-user full-duplex cooperative non-orthogonal multiple access (FD-CNOMA) network, presenting closed-form expressions for the outage probability (OP) and effective capacity (EC) of both users. The analytical results indicate that an increased signal-to-noise ratio (SNR) corresponds to a reduced OP and heightened EC, signifying enhanced communication quality. We analyze the OP and EC under two cases: R1=2R2 and R1=R2. Our analytical expressions reveal that both θ and ρ significantly impact the effective capacities. To validate these analytical findings, Monte Carlo simulations are performed, demonstrating alignment between theoretical insights and practical outcomes. The results underscore the critical role of SNR in influencing network performance, providing valuable insights into optimizing communication quality in FD-CNOMA systems.
Field-programmable gate array-based field-oriented control for permanent magnet synchronous motor drive Nam Duong Le; Le Quang Linh; Nguyen Tien Huy Cong; Phuong Vu; Tung Lam Nguyen
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.v21i2.23560

Abstract

Permanent magnet synchronous motor (PMSM) is a special type of synchronous electric motor that has many applications such as in the manufacturing industry of robots, self-propelled mechanisms, in the medical fiel. In this paper, the permanent magnet synchronous motor motor control structure according to the field-oriented control (FOC) algorithm will be implemented on the field-programmable gate array (FPGA) card. Function blocks in FOC algorithm for example PI controller, space vector pulse width modulation (SVPWM) algorithm will be integrated into individual itegrated circuit (Ics) then will be connected to form an IC with the function of implementing FOC algorithm. Furthermore, this algorithm will be used for powertrains using gallium nitride (GaN). GaN technology provides switching frequencies up to 100 kHz instead of the upper 2 to 20 kHz like insulated gate bipolar transistor (IGBT) transistors. With GaN technology, it is possible to reduce switching losses as well as increase the efficiency of the power converter. The performance results will be verified through the typhoon hardware in the loop (HIL) device.
The use of dolomite to overcome grounding resistance in acidic swamp land Dian Eka Putra; Muhammad Irfan Jambak; Zainuddin Nawawi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 3: June 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i3.26656

Abstract

This research addresses the effectiveness of grounding systems in acidic swampland, which poses a challenge in protecting people and electrical equipment from the risk of electric shock. The increasing use of swampland for electrical installations necessitates a solution to reduce the high grounding resistance resulting from poor soil resistivity values. This study proposes using dolomite as an admixture to improve soil conductivity and lower grounding resistance. Experimental methods were conducted by embedding rod electrodes of various materials in dolomite-mixed media with varying compositions. The results showed that adding dolomite significantly decreased the grounding resistance, although there were inconsistencies in the test results; on average, the decrease in resistance reached 25%. Galvanized electrodes proved to be the most effective in this system. These findings provide new insights in the field of grounding systems and offer practical solutions that are environmentally friendly and sustainable. This research is expected to be an important reference for developing more innovative and effective grounding system techniques in the future.
Development of triangular array eight patches antennas for circularly-polarized synthetic aperture radar sensor Muhammad Fauzan Edy Purnomo; Vita Kusumasari; Edi Supriana; Rusmi Ambarwati; Akio Kitagawa
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.v18i2.14759

Abstract

In this paper, we obtain the left-handed circularly polarized (LHCP) and right-handed circularly polarized (RHCP) of triangular array eight patches antennas using corporate feeding-line for circularly polarized-synthetic aperture radar (CP-SAR) sensor embedded on unmanned aerial vehicle (UAV) with compact, simple, and efficient configuration. Although the corporate feeding-line design has already been developed, its design was for the side antenna view of 0° and only produced one of LHCP or RHCP instead of both. Here, the design for LHCP and RHCP eight patches array fed by corporate feeding-line having the side antenna view of 36° at f=1.25 GHz for CP-SAR are discussed. We use the 2016 version of computer simulation technology (CST) to realize the method of moments (MoM) for analyzing. The performance results, especially for gain and axial ratio (Ar) at resonant frequency are consecutively 13.46 dBic and 1.99 dB both of LHCP and RHCP. Moreover, the 12-dBic gain-bandwidth and the 3-dB Ar-bandwidth of them are consecutively around 38 MHz (3.04%) and 6 MHz (0.48%). Furthermore, the two-beams appeared at boresight in elevation plane for average beamwidth of 12 dBic-gain and the 3 dB-Ar LHCP and RHCP have similar values of around 12° and 46°, respectively.
A compact multiband antenna based on metamaterial for L-band, WiMax, C-band, X-band, and Ku-band applications Youssef Frist; Mourad Elhabchi; Mohamed Nabil Srifi
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.v22i1.25204

Abstract

A novel multiband metamaterial (MTM) unit cell antenna loaded with split ring resonator (SRR) slots that resonates at seven bands, which are (1.91 GHz), (3.6 GHz), (6.25 GHz), and (8.69 GHz, 9.69 GHz, 10.70 GHz), and 12.33 GHz of the spectrum, making it suitable for L-band, worldwide interoperability for microwave access (WiMax), C-band, X-band downlink, and Ku-band applications, respectively, is proposed and discussed in this work. The proposed antenna has a very compact size of 14×15×1.6 mm3 with an FR4 substrate. The simulation results show that the presented antenna attains a reflection coefficient of less than -10 dB (S11 -10 dB) and a radiation pattern across all operating bands. In addition, the suggested antenna provides good gains over the resonant frequency signals with an average of 6.75 db. The antenna simulations and parametric studies have been done using both computer simulation technology microwave studio (CST microwave studio) and high frequency structure simulator (HFSS) to confirm the obtained simulation results.
Towards more accurate and efficient human iris recognition model using deep learning technology Bashra Kadhim Oleiwi Chabor Alwawi; Ali Fadhil Yaseen Althabhawee
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 4: August 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i4.23759

Abstract

In this study, an end-to-end human iris recognition system is presented to automatically identify individuals for high level of security purposes. The deep learning technology based new 2D convolutional neural network (CNN) model is introduced for extracting the features and classifying the iris patterns. Firstly, the iris dataset is collected, preprocessed and augmented. The dataset are expanded and enhanced using data augmentation, histogram equalization (HE) and contrast-limited adaptive histogram equalization (CLAHE) techniques. Secondly, the features of the iris patterns were extracted and classified using CNN. The structure of CNN comprises of convolutional layers and ReLu layers for extracting the features, pooling layers for reducing the parameters, fully connected layer and Softmax layer for classifying the extracted features into N classes. For the training process and updating the weights, the backpropagation algorithm and adaptive moment estimation Adam optimizer are used. The experimental results carried out based on a graphics processing unit (GPU) and using Matlab. The overall training accuracy of the introduced system was 95.33% with a consumption time of 17.59 minutes for training set. While the testing accuracy 100% with a consumption time of 12 seconds. The introduced iris recognition system has been successfully applied.
Network traffic analysis and bandwidth forecasting for using Meta’s Prophet: a case study Yusuf Onimisi Isaac; Ayodeji James Bamisaye; Ijagbemi Adedotun; Theophilus Olusegun Dada; Onyemenam Obiajulu John
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 3: June 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i3.27609

Abstract

This study created a forward-looking bandwidth prediction system for students’ halls of residence at Landmark University. The system uses Meta’s Prophet, a method for analyzing patterns in data over time, and was trained on past internet traffic data from October to December 2024. The system was able to predict future bandwidth usage with over 90% accuracy. To assess how well the system worked, several common metrics were used, including mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). The MAE was calculated as 10,099,863.10 bits per second (bps), and the RMSE was 13,570,959.58 bps. While the mean squared error (MSE) appears large numerically, this is anticipated due to the size of the bandwidth data involved in its calculation. Importantly, the prediction errors are considered reasonable when considered in relation to the actual peak bandwidth usage, which fluctuated between 47 and 50 megabits per second (Mbps). These findings suggest that machine learning can be a valuable tool for refining network infrastructure and improving the user experience quality of service (QoS) in environments with many users, such as university residences.

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