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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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Hybrid unipolar-bipolar system with quasi-polarized code for free-space optical communication Eddy Wijanto; Kevin Sutanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 3: June 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i3.25848

Abstract

In this study, the hybrid unipolar-bipolar (U-B) optical code division multiple access (OCDMA) with mixed unipolar-bipolar scheme in free-space optical communication was proposed. Additionally, the codeword assigned introduced the quasi-polarized code, which could be used to transmit both the unipolar and bipolar section. Using OptiSystem simulations, the model was studied. According to the results from the simulation, the proposed hybrid UB OCDMA can correctly decode the original optical signal from its matching encoder. Further testing of the hybrid U-B OCDMA system was conducted in turbulence conditions. According to the simulation results, walsh-zero cross correlation (ZCC) performs better than all other codes for the unipolar segment whereas walsh-hadamard (W-H) code performs best for the bipolar section. The simulations also showed that the performance deterioration of the walsh-ZCC algorithm was the greatest.
An intelligent strabismus detection method based on convolution neural network Haider Shamil Hamid; Bassam AlKindy; Amel H. Abbas; Wissam Basim Al-Kendi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 6: December 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i6.24232

Abstract

Strabismus is one of the widespread vision disorders in which the eyes are misaligned and asymmetric. Convolutional neural networks (CNNs) are properly designed for analyzing images and detecting texture patterns. In this paper, we proposed a system that uses deep learning CNN applications for automatically detecting and classifying strabismus disorder. The proposed system includes two main stages: first, the detection of facial eye segmentation using the viola-jones algorithm. The second stage is to map the segmented eye area according to the iris position of each eye. This method is applied to three strabismus datasets, gathered as digital images. The second section covers the segmentation of the eye region. Besides, the evaluation equations for measuring system performance. The system has undergone numerous experiments in various stages to simulate and analyze the detection performance of CNN layers through different classifiers and variant thresholds ratio. The researchers investigated the experimental outcomes during the training and testing phases and obtained promising results that exhibit the effectiveness of the proposed system. According to the results, the accuracy of this technique reached 95.62%.
Dual band antenna design for 4G/5G application and prediction of gain using machine learning approaches Narinderjit Singh Sawaran Singh; Md. Ashraful Haque; Redwan A. Ananta; Md. Sharif Ahammed; Md. Abdul Kader Jilani; Liton Chandra Paul; Rajermani Thinakaran; Malathy Batumalay; JosephNg Poh Soon; Deshinta Arrova Dewi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 2: April 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i2.26233

Abstract

In this research, we disclose our findings from exploring a machine learning (ML) approach to enhancing the antenna’s performance in Industrial and Innovation contexts, particularly for4G and 5G (n77, n78) contexts. Methods for evaluating antenna performance utilizing simulation, the resistor, inductor, and capacitor (RLC) equivalent circuit model, and ML are discussed. Gain is a maximum of 6.56 dB and efficiency is about 97% for this antenna. The predicted antenna gain is calculated using an alternative supervised regression ML technique. Multiple measures, including as the variance score, R-square (R2), mean square error (MSE), and mean absolute error (MAE), can be used to assess an ML model’s performance. The linear regression (LR) model predicts profit with the fewest errors and highest accuracy of the five ML models. Finally, computer simulation technology (CST) and advanced design system (ADS) modeling findings, along with ML results, show that the proposed antenna is a promising option for 4G and 5G applications.
Sparse Representation for Detection of Microcalcification Clusters Xinsheng Zhang; Minghu Wang; Ji Ma Ji Ma
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 3: September 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i3.835

Abstract

We present an approach to detect MCs in mammograms by casting the detection problem as finding sparse representations of test samples with respect to training samples. The ground truth training samples of MCs in mammograms are assumed to be known as a priori. From these samples of the interest object class, a vocabulary of information-rich object parts is automatically constructed. The sparse representation is computed by the l1-regularized least square approach using the interior-point method. The method based on sparse representation expresses each testing sample as a linear combination of all the training samplesfrom the vocabulary. The sparse coefficient vector is obtained by l1-regularized least square through learning. MCs detectionis achieved by defining discriminatefunctions from the sparse coefficient vector for each category. To investigate its performance, the proposed method is applied to DDSM datasets and compared with support vector machines (SVMs) and twin support vector machines (TWSVMs). The experimental results have shown that the performance of the proposed method is comparable with or better than those methods. In addition, the proposed method is more efficient than SVMs and TWSVMs based methods as it has no need of model selection and parameter optimization.
Reflector antenna design in different frequencies using frequency selective surfaces Shahir Fleyeh Nawaf; Lujain S. Abdulla; Abdulmutalib A-Wahab Husein
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 5: October 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i5.25016

Abstract

In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Planar broadband antenna for 2G/3G systems Ashutosh Singh Chauhan; Priyansh Kasyap; Ankit Gupta; Debani Prasad Mishra; Surender Reddy Salkuti; Seong-Cheol Kim
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.v20i3.18977

Abstract

A planar antenna with broadband gestalt is presented for mobile networks. The structure of the antenna is made up of a folded dipole pair with an L-figure microstrip coupling line. The microstrip coupling along with the dipoles are attached on a similar substrate. The radiation parts are plotted at 1.7 GHz, 2.2 GHz, and 2.7 GHz. A flexible coaxial cable made of perfect electric conductor (PEC) material is attached to the L-figure microstrip whereas the outside conductor made up of RO4350B material is attached to the coplanar strip of line. The gain of the antenna is almost 9 dBi. The benefit of the planar structure is that it offers a simple feeding structure and compact size that is necessary for second generation (2G)/third-generation (3G)/long-term evolution (LTE) systems. Finally, the antenna proposed is designed by using computer simulation technology (CST) microwave studio.
Improving multilabel classification of hate speech and abusive language in Indonesian using MAML Jasman Pardede; Ghixandra Julyaneu Irawadi; Rizka Milandga Milenio
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.v24i2.27332

Abstract

This study investigates automated multi-label detection of hate speech and abusive language (HSAL) in Indonesian social media, addressing challenges of data imbalance, especially in minority labels. Two training approaches are compared: standard supervised learning and meta-learning using the model-agnostic meta-learning (MAML) algorithm. IndoBERTweet-BiGRU is adopted as the baseline model, while MAML is leveraged to enhance generalization and adaptability with limited training data. Both models are trained on a multilabel dataset with 13 HSAL categories exhibiting highly imbalanced distributions. The best supervised model achieved an F1-Micro of 84.02% and an F1-macro of 77.97%, whereas the best MAML-trained model reached 84.12% and 76.85%, respectively. Although the overall gap is small, MAML demonstrates notable improvements on minority classes such as hate speech (HS) physical, gender, and race, shown through higher F1-score and area under the receiver operating characteristic curve (AUROC) values. These results highlight its strength in low-resource classification settings. This study is limited to Indonesian language and YouTube transcript contexts, and MAML incurs higher training complexity. Cultural and linguistic nuances also present potential bias in real-world use. Despite these constraints, the proposed system offers practical benefits by enabling fine-grained HSAL classification and supporting earlier detection of harmful online content.
Overview of the progression of state-of-the-art language models Asmae Briouya; Hasnae Briouya; Ali Choukri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.25936

Abstract

This review provides a concise overview of key transformer-based language models, including bidirectional encoder representations from transformers (BERT), generative pre-trained transformer 3 (GPT-3), robustly optimized BERT pretraining approach (RoBERTa), a lite BERT (ALBERT), text-to-text transfer transformer (T5), generative pre-trained transformer 4 (GPT-4), and extra large neural network (XLNet). These models have significantly advanced natural language processing (NLP) capabilities, each bringing unique contributions to the field. We delve into BERT’s bidirectional context understanding, GPT-3’s versatility with 175 billion parameters, and RoBERTa’s optimization of BERT. ALBERT emphasizes model efficiency, T5 introduces a text-to-text framework, and GPT-4, with 170 trillion parameters, excels in multimodal tasks. Safety considerations are highlighted, especially in GPT-4. Additionally, XL-Net’s permutation-based training achieves bidirectional context understanding. The motivations, advancements, and challenges of these models are explored, offering insights into the evolving landscape of large-scale language models.
BBO tuned PI controller for the stability of TCP networks Manal Hadi Jaber; Manal Kadhim Oudah; Mohammed Qasim Sulttan; Salam Waley Shneen
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.v21i2.21795

Abstract

The congestion is the most important issue that effects on the performance of data transition over internet networks. One of the important techniques developed is active queue management (AQM) that prepares an efficient congestion control by reducing losing packets, queue size, and energy consumption. Therefore, AQM technique deemed as a base of many congestion control algorithms schemes. This work suggested the using of proportional integral (PI) controller as an AQM and then use an optimized control system such as biogeography-based optimization (BBO) with PI controller as (BBO-PI). The optimal control (BBO-PI) is characterized by access to design and fine-tuning of defining the shapes of the optimal parameters of PI controller. The BBO algorithm was implemented by using the mathematical system model by M-file/Matlab and Simulink. The simulation results showed the best performance for the transmission control protocol (TCP) network when compared the system with using the PI controller and using optimal control (BBO-PI), the ratio of enhancing the system with using of BBO-PI better than using a PI controller only in terms of rising time is 1.11, settling time is 2.85 and overshooting is 85%. Therefore, the proposed method was very fast and required few iterations.
A multiband sub-6 THz patch antenna with high gain for IoT and 6G communication Redwan Al Mahmud Bin Asad Ananta; Md. Sharif Ahammed; Md Ashraful Haque; Narinderjit Singh Sawaran Singh; Kamal Hossain Nahin; Jamal Hossain Nirob; Md. Kawsar Ahmed; Liton Chandra Paul
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.v23i3.26551

Abstract

This comprehensive study introduces a meticulously designed and characterized terahertz (THz) multiple-input multiple-output (MIMO) antenna engineered to operate within the 0.4 THz to 1.6 THz frequency range. The antenna’s construction includes a copper patch and ground plane integrated into a polyimide substrate, ensuring exceptional durability and robust performance. Significantly, the antenna reveals four distinct resonance frequencies at 0.46 THz, 0.9 THz, 1.31 THz, and 1.44 THz each accompanied by bandwidths of 0.005 THz, 0.17 THz, and 0.34 THz, respectively. Moreover, the antenna delivers notable gains of 8.52 dB, 11.54 dB, and 13.25 dB at these frequencies, coupled with substantial efficiencies of 88.32%, 92.02%, and 89.89%, respectively. Additionally, the antenna showcases exceptional isolation of 26 dB, a low envelope correlation coefficient (ECC) of 0.003, and a diversity gain (DG) of 9.98. These remarkable attributes underscore the antenna’s aptness for high-performance THz applications, offering substantial advantages in terms of gain, efficiency, and isolation for next-generation wireless communication systems.

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