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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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A secure telemedicine electronic platform based on lightweight cryptographic approach Israa Ezzat Salem; Haider Rasheed Abdulshaheed; Hassan Muwafaq Gheni
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.v20i5.22662

Abstract

Telemedicine platforms have emerged as one of the most harnessed studies in recent years, especially after the spread of pandemics. Due to the epidemic, telemedicine distribution to rural or isolated areas has become an urgent need. However, there are several obstacles to providing remote medical care, the most significant of which is protecting patient data while sustaining the speed of communication between the patient and the medical staff. The significant of this study is to provides a lightweight encryption/decryption technique that uses on the internet of medical things in stance of bio-sensors and bio-actuators. This study is one of the cybersecurity approaches, such type of encryption has little effect on the speed of data transmission. The Diffie Hellman technique is used as a lightweight encryption method because it includes four encryption-keys. The efficiency of the proposed encryption method has been compared with several equivalent methods. According to experimental results, the proposed encryption method represents a lightweight and secure method which can accomplish the level of protection that required to secure medical information despite the data’s disarray.
Predictive safety helmet for miners using internet of things and artificial intelligence Vijayalakshmi Murugesan; Irudhaya Ronisha Innasi John Benedict; Janani Vigneswaran; Pooja Senthamarai Kannan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 4: August 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i4.27421

Abstract

Mining is still responsible for many deaths since mines have dangerous environmental conditions including mine collapses, gas emissions, and high temperatures. However, traditional helmets do not provide adequate protection; besides, they cannot analyze miners’ health as well as the environmental hazards. In order to solve this issue, this work presents a predictive safety helmet equipped with several sensors and means of communication. Specifically, the helmet comprises a micro-electro mechanical systems (MEMS) accelerometer for vibration monitoring, a gas sensor for detecting the presence of harmful gases, a heartbeat sensor for assessing workers’ well-being, and a temperature sensor for monitoring the environmental parameters. Additionally, the device is provided with a global positioning system (GPS) module for location determination and a global system for mobile (GSM) module for transmitting alert notifications in case of emergency situations. The collected data is analyzed on an internet of things (IoT)-based system; any signs of danger cause alerts to be sent immediately.
Modeling and optimization of artificial magnetic conductor on the performance of on-chip-antenna for 28 GHz devices Ahmadu Girgiri; Mohd Fadzil Ain; Mohd Zamir Pakhuruddin; Mohamad Faiz Mohamed Omar; Bello Muhammad Abdullahi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26443

Abstract

The growing popularity of chip-based devices has spurred interest in developing on-chip antennas (OCAs). However, low gain and poor radiation characteristics have been significant challenges. Integrating an artificial magnetic conductor (AMC) into the oxide layer is an alternative. This article presents a new AMC model that improves the performance of 28 GHz OCA using dual-rectangular-patch (DRP) as unit cells. The DRP parameters, patch width (Pw), patch gap (Pg), and substrate height (hs) were used to control the AMC characteristic. Two numerical equations for gain (G) and efficiency (η) have been developed to evaluate the new model’s performance. The impact of parameters on the antenna’s gain and radiation efficiency was equally analyzed. A prototype antenna was fabricated and tested to validate the model. It demonstrated a peak gain of 3.69 dB and radiation efficiency of 67.18%, with an achieved impedance bandwidth of 1.27 GHz, making it well-suited for 28 GHz device applications. Furthermore, the equations formulated provide the research community with a straightforward method to calculate the gain and efficiency of a 28 GHz antenna. This method is not limited to on-chip antennas but can also be applied to off-chip antennas if DRP-AMC is implemented.
Neuro-fuzzy-based anti-swing control of automatic tower crane Saleh B. Al-Tuhaifi; Kasim Mousa Al-Aubidy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 4: August 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i4.24044

Abstract

Controlling the position of the final load and the anti-swing control of the loads during the operation of the tower crane are challenging tasks. These are the most important control issues for safe operation, which are difficult to achieve easily with conventional control systems. Hence, the need to integrate the concepts of soft-computing into the tower crane control system. The aim of this research work is to design an adaptive-network-based fuzzy inference system (ANFIS) controller to move the payload to the final position with the lowest possible swing angle. To evaluate the ability of the proposed controller to meet the control requirements, its performance was compared to three other controllers: a conventional proportional derivative (PD) controller, a fuzzy-tuned PD controller and a fuzzy controller. MATLAB-based computer simulations of the crane and controllers were carried out to verify and compare the performance of the proposed controllers. The obtained results show the effectiveness of the ANFIS-based controller in adjusting the load position while keeping the load fluctuations small at the final position. The load oscillation angle is about ±2.28° with the ANFIS controller while it is about ±10° when using the PD controller. In addition, only one ANFIS controller is used for both load position and swing angle control.
Network and layer experiment using convolutional neural network for content based image retrieval work Fachruddin Fachruddin; Saparudin Saparudin; Errissya Rasywir; Yovi Pratama
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.19759

Abstract

In this study, a test will be conducted to find out how the results of experiments on the network and layer used on the convolutional neural network algorithm. The performance and accuracy of the retrieval process method that was tested using the algorithm approach to do an object image retrieval. The expected results of this study are the techniques offered can provide relatively better results compared to previous studies. The results of the classification of object images with different levels of confusion on the Caltech 101 database resulted an average accuracy value. From the experiments conducted in the study, content based image retrieval work (CBIR) work using convolutional neural network (CNN) algorithm in terms of execution time, loss testing and accuracy testing. From several experiments on layers and networks shows that, the more hidden layers used, then the result is better. The graph of validation loss decreases at fewer epochs, slightly fluctuating at more epochs. Likewise, validation accuracy increases insignificantly on epochs with small amounts, but tends to be stable on more epochs.
Metamaterial-enhanced four-port MIMO antenna for 5G communications at 28/38 GHz Remili Fatima; Bouttout Farid; Djellid Asma
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.v23i6.27311

Abstract

This work presents a novel compact four-port multiple-in multiple-out (MIMO) antenna enhanced with metamaterial unit cells for 5G millimeter-wave (mmWave) applications at 28 and 38 GHz. Compact MIMO antennas at mmWave bands often suffer from high mutual coupling, which degrades isolation and diversity performance. To address this, the proposed design integrates metamaterial loading around each radiating element to effectively suppress coupling, enhance isolation, and improve overall efficiency. The antenna, measuring 27×27×0.8 mm³, is implemented on a flexible FR4_epoxy substrate (εr=4.4), enabling compatibility with portable and embedded devices. Full-wave simulations performed in both ANSYS high-frequency structure simulator (HFSS) and computer simulation technology (CST) studio suite confirm the effectiveness of the approach, achieving an exceptionally low envelope correlation coefficient (ECC) (0.0001), a fivefold reduction in channel capacity loss (CCL), and a wide impedance bandwidth of 25.90–34.93 GHz with |S11| below −10 dB in both operating bands. The design also exhibits stable directional gain and low sidelobes. Compared with recent compact MIMO antennas reported in the literature, the proposed configuration offers significantly improved isolation, bandwidth, and mechanical flexibility. These features make it a strong candidate for integration into high-capacity 5G modules, portable terminals, and compact internet of things (IoT) communication systems.
Advancements in accurate speech emotion recognition through the integration of CNN-AM model Marion Olubunmi Adebiyi; Timothy T. Adeliyi; Deborah Olaniyan; Julius Olaniyan
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.v22i3.25708

Abstract

In this study, we introduce an innovative approach that combines convolutional neural networks (CNN) with an attention mechanism (AM) to achieve precise emotion detection from speech data within the context of e-learning. Our primary objective is to leverage the strengths of deep learning through CNN and harness the focus-enhancing abilities of attention mechanisms. This fusion enables our model to pinpoint crucial features within the speech signal, significantly enhancing emotion classification performance. Our experimental results validate the efficacy of our approach, with the model achieving an impressive 90% accuracy rate in emotion recognition. In conclusion, our research introduces a cutting-edge method for emotion detection by synergizing CNN and an AM, with the potential to revolutionize various sectors.
Cloud-based control system: a bibliometric analysis Santo Wijaya; Harco Leslie Hendric Spits Warnars; Ford Lumban Gaol; Benfano Soewito
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.v20i6.23666

Abstract

Network control system (NCS) approaches for distributed closed-loop control systems have been established in industrial control. However, recent advancements in cloud computing provide scalable, elastic, and low-cost networked computing capabilities over the internet, which can be utilized as an extension of NCS, in this term, cloud-based control systems (CCS) with a potential replacement of the controller. The main objective of this research is to use bibliometric analysis to obtain insight into diachronic productivity, the significant effect of the published information on the research network, and research trends based on term co-occurrences of the CCS domain. The literature study employs the PRISMA method to construct necessary inclusion criteria such as keywords, databases, publication year, accessibility, and primary article, then Publish or Perish is used to generate RIS formatted file for network analysis of co-authorship and term co-occurrence with VOSviewer. The results showed that Yuanqing Xia was the most prolific author in terms of the total published article and total citations received, China was the country with the highest publication output, and Elsevier was the publisher with the most significant impact factor. CCS emerged in 2012, and current research trends include control system architecture, controller, algorithm, stability, and approach on intelligent manufacturing.
Imposing neural networks and PSO optimization in the quest for optimal ankle-foot orthosis dynamic modelling Annisa Jamali; Aida Suriana Abdul Razak; Shahrol Mohamaddan
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.v23i2.25876

Abstract

Individuals with abnormal walking patterns due to various conditions face significant challenges in daily activities, especially walking. Ankle-foot orthosis (AFO) devices are crucial in providing essential support to their lower limbs. Accurately modeling the dynamic behavior of AFO systems, particularly in predicting ground reaction forces, is a complex yet vital task to ensure their effectiveness. This research develops dynamic models for AFO systems using advanced modeling techniques, employing both parametric and non-parametric approaches. Parametric methods, such as particle swarm optimization (PSO), and non-parametric methods, like multi-layer perceptron (MLP) neural networks, are utilized through system identification methods. According to the findings, the MLP neural network continuously generates objective results and performs exceptionally well in correctly detecting the AFO system, attaining a noticeably lower mean squared prediction error of 0.000011. This research highlights the potential of advanced modeling techniques, particularly MLP neural networks, in enhancing AFO system modeling accuracy. Although parametric techniques like PSO are useful, the MLP approach performs better, offering insightful information about modelling AFO systems and indicating that non-parametric techniques like MLP neural networks have potential to further AFO creation and control.
Numerical Simulation of Chip Formation in Metal Cutting Process Zhao Yongjuan; Pan Yutian Pan Yutian; Huang Meixia
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.v10i3.827

Abstract

In order to study the chip formation mechanism in metal cutting process, based on finite element software ABAQUS, the paper established finite element model and carried out numerical simulation on serrated chip formation of Ni-base superalloy GH4169 and ribbon chip formation of 45# steel respectively. In addition, this paper also analyzed the influence law of three factors (cutting speed, feed rate, back cutting depth) on cutting force and the distribution rule of cutting heat in serrated chip formation of GH4169.

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