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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 26 Documents
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Search results for , issue "vol 22, no 2: april 2024" : 26 Documents clear
Real time pedestrian and objects detection using enhanced YOLO integrated with learning complexity-aware cascades Ahmed Lateef Khalaf; Mayasa M. Abdulrahman; Israa Ibraheem Al_Barazanchi; Jamal Fadhil Tawfeq; Poh Soon JosephNg; Ahmed Dheyaa Radhi
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.v22i2.24854

Abstract

Numerous technologies and systems, including autonomous vehicles, surveillance systems, and robotic applications, rely on the capability to accurately detect pedestrians to ensure their safety. As the demand for real-time object detection continues to rise, many researchers have dedicated their efforts to developing effective and trustworthy algorithms for pedestrian recognition. By integrating learning complexity-aware cascades with an enhanced you only look once (YOLO) algorithm, the paper presents a real-time system for identifying both items and pedestrians. The performance of the proposed approach is evaluated using the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) pedestrian dataset across both the v4 and v8 versions of the YOLO framework. Prioritizing both speed and accuracy, the enhanced YOLO algorithm outperforms its baseline counterpart. The demonstrated superiority of the suggested technique on the KITTI pedestrian dataset underscores its effectiveness in real-world contexts. Furthermore, the complexity-aware learning cascades contribute to a streamlined detection model without compromising performance. When applied to scenarios requiring real-time identification of objects and individuals, the proposed method consistently delivers promising outcomes.
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets Maha A. Rajab; Firas A. Abdullatif; Tole Sutikno
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.v22i2.25840

Abstract

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classification by adapting VGG-16 net and VGG-19 net models and subsequently identifying the optimal performer between the two nets during the classification process. A publicly available dataset comprising 500 images categorized into 5 distinct classes (100 images per class), was utilized in this work. The obtained empirical outcomes demonstrate a remarkable accuracy rate of 99.6% for the VGG-16 net model, while VGG-19 net achieves a 100% accuracy rate. Based on these findings, it can be inferred that VGG-19 net exhibits superior performance in classifying images of grapevine leaves compared to the VGG-16 net.
Hybrid technique for optimal task scheduling in cloud computing environments Nihar Ranjan Sabat; Rashmi Ranjan Sahoo; Manas Ranjan Pradhan; Biswaranjan Acharya
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.v22i2.25641

Abstract

Since cloud computing has an abundance of users, the system has to execute a wide range of tasks. Task scheduler methods that are both robust and efficient while delivering the best outcomes are required. The task volume and runtime in the cloud vary rapidly, making task assessment and resource mapping difficult. Security issues, communication delays, and data loss are substantial barriers to scheduling. Furthermore, optimization techniques can be utilized to reduce load and assign tasks so that the user can finish tasks faster. This paper offers a hybrid job scheduling technique for cloud computing using adaptive particle swarm optimization and ant colony optimization particle swarm optimization-ant colony optimization (adaptive PSO-ACO). After rapidly finding the initial solution via particle swarm optimization, the ant colony optimization approach establishes its first pheromone distribution. The suggested hybrid algorithm is compared to standalone PSO and ACO algorithms. Compared to ACO, the percentage decrease is 7.9%. Hybrid method has the lowest total cost, 55% less compared to PSO. Tasks vary when virtual machines (VMs) are constant and VMs vary when tasks are constant. Parameters like final cost, makespan, fitness value, computation time and weighted time are assessed to evaluate the performance of the hybrid task scheduling algorithm.
Model predictive control combined reinforcement learning for automatic vehicles applied in intelligent transportation system Vo Thanh Ha; Chu Thi Thuy
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.v22i2.25274

Abstract

This paper presents the design of model predictive control (MPC) combined reinforcement learning (RL) applied in an intelligent transportation system (ITS). The car is to follow the reference path by the MPC control, and its parks in the parking by RL has been trained. The MPC controller constantly moves the vehicle along the reference path while the MPC algorithm searches for an empty parking spot. Meanwhile, the reinforcement learning-proximal policy optimization (RL-PPO) control will perform parking on demand if the MPC finds a parking position. This hybrid controller can quickly implement programming on MATLAB software by writing code. Furthermore, this hybrid controller simultaneously performs precise detection and avoidance of obstacles in tight parking spaces. The correctness of the theory is demonstrated through MATLAB/Simulink.
Quantum binary particle swarm optimization for optimal on-load tap changing and power loss reduction Aji Akbar Firdaus; Irrine Budi Sulistiawati; Vicky Andria Kusuma; Dimas Fajar Uman Putra; Hamzah Arof; Novian Patria Uman Putra; Sena Sukmananda Suprapto
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.v22i2.25744

Abstract

Over time, there has been a continuous surge in the demand for electrical energy, necessitating the development of larger and more intricate electrical power networks. These extensive networks pose a significant challenge, primarily in the form of considerable loss of electrical energy, which, if not effectively addressed, may lead to persistent and imperceptible losses. In response to this challenge, this research proposes the application of quantum binary particle swarm optimization (QBPSO) for the coordinated management of on-load tap changers (OLTC) in loaded transformers within a distribution network, with a specific emphasis on reducing power losses. The experimental results demonstrate that the implementation of QBPSO results in a reduction of power loss from 21.756107 kW to 19.157321 kW and an increase in the average voltage from 19.00467941 kV to 19.93068 kV in a 20 kV 34-bus distribution network. This has the potential to significantly enhance overall system efficiency.
Comparative analysis of call admission control techniques for efficient resource utilization and QoS in IEEE 802.16e network Ifeanyi Chinaeke-Ogbuka; Bonaventure Ekengwu; Christantus Nnamani; Joy Eneh
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.v22i2.25591

Abstract

In order to provide solution to limited network resources in heterogeneous wireless networks supporting different applications with distinct quality of service (QoS) requirements, call admission control (CAC) schemes are implemented. This work is aimed at investigating three mostpopular CAC schemes employedin mobile worldwide interoperability for microwave access (WiMAX), namely dynamic CAC with bandwidth reservation (DCACBR), QoS-aware CAC (QoSACAC), and QoS guaranteed CAC (QoSGCAC) to identify their shortfalls which will form the focus of future research. A general platform is developed and simulated. The simulation was based on the following KPIs: blocking rate, dropping rate, and throughput for new and handoff connections. Simulation results for new connection shows that QoSGCAC outperforms scheme DCACBR and QoSACAC, having 26.9% and 8.56% improvements in throughput and 63.11% and 24.17% in blocking rate respectively. For handoff connection, QoSACAC showed the best performance having 13.25% and 47.84% improvements in throughput and 6.8% and 49.3% in blocking rate as compared to the DCACBR and QoSGCAC, respectively. Result analysis shows that QoSACAC has the best performance however, it admits new connections and degrade existing connections but failed to consider the delay-intolerant service classes. It is recommended that the QoSACAC be further improved.
5G-backed resilience and quality enhancement in internet of medical things infrastructure for resilient infrastructure Noora Jamal Ali; Noor Amer Hamzah; Ahmed Dheyaa Radhi; Yitong Niu; Poh Soon JosephNg; Jamal Fadhil Tawfeq
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.v22i2.24863

Abstract

The internet of medical things (IoMT) has transformed the healthcare sector by facilitating real-time monitoring, remote patient care, and tailored healthcare solutions. However, the challenge of upholding a high standard quality of service (QoS) in IoMT implementations remains a pressing issue. This article delves into the possibilities of utilizing 5G networks and smart techniques to optimize QoS within IoMT systems. By capitalizing on the capabilities of 5G networks, including substantial bandwidth, minimal latency, and extensive connectivity, in conjunction with intelligent methods such as machine learning and predictive analytics, this paper introduces novel strategies to enhance QoS in IoMT environments. The summary underscores the advantages of these methods in elevating network dependability, diminishing latency, enhancing data transmission efficiency, and enabling resource allocation efficiency in IoMT deployments. Additionally, it explores the potential ramifications of these developments on healthcare outcomes, patient contentment, and the overall effectiveness of the healthcare system. The conclusions propose that by maximizing QoS through 5G networks and intelligent techniques, IoMT holds the potential to significantly enhance the delivery of healthcare services, fostering a more interconnected and efficient healthcare ecosystem in the process innovation.
Optimal placement of distributed generations on distribution network for reducing power loss and improving feeder balance Huu Truong Trinh; Thuan Thanh Nguyen
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.v22i2.25683

Abstract

The suitable placement and power of distributed generation (DG) can bring technical benefits to the distribution network. This paper applies the Coot optimization algorithm to the DG placement problem with the goal of minimizing power loss and feeder balancing load (LBF). The weight method is used to combine the membership objectives. The evaluation results on the network of 70 nodes for different weight values of the objective function show that the optimal power and installation location of DGs significantly reduces power loss and improves LBF index. In this study, eleven cases were considered. As the weight of power loss part ?1 increases from 0 to 1, the power loss gradually decreases, the LBF index gradually increases, the maximum current gradually decreases, and the minimum voltage amplitude gradually improves. Comparing the results of Coot with particle swarm optimization (PSO) shows that the indicators are improved. In the three cases where ?1 is 0, 0.5, and 1, power loss gained by Coot compared to PSO is less than 47.2663 kW, 73.2725 kW, 30.8708 kW, respectively. LBF index of Coot compared to PSO is less than 98.2%, 88.2%, 81.9%, respectively. The maximum, minimum, average, standard deviation, and CPU time of Coot are smaller than those of PSO. So, Coot is one of the promising methods for this problem.
The design and optical properties of orthosilicate phosphor-bredigite-like structure as a green light component in WLED device Ha Thanh Tung; Nguyen Le Thai; My Hanh Nguyen Thi; Huynh Thanh Thien
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.v22i2.25286

Abstract

We produce the green phosphor Ca14-xEuxMg2[SiO4]8 (CEMSO) to be a part of the white light emitting diodes (WLEDs), short for diodes that generate white illumination. It has wide emission spectra, reaching highest value as 505 nm when excited at the wavelength of 400 nm, which is caused by the 4f 65d–4f 7 shift (excited state to ground state) in an ion of Eu2+. The dipole-dipole interactivity appeared to be main energy shift method for the electric multipolar nature in CEMSO. We determine the critical distance to be 12.9 Å as well as 14.9 Å via a critical Eu2+ concentration and theory of Dexter regarding the energy shift. The CEMSO is integrated into the phosphor compound of yellow-phosphor/silicone for producing the UV-LED (395 nm). The impacts of CEMSO concentrations on UV-LED performances are determined. Significant improvements in chromatic uniformity and luminous output of the WLED are reported. The color rendering index (CRI) is not promoted, but this can be addressed by combining CEMSO green phosphor with red-luminescence materials, for example, red quantum dots or red phosphors.
Chain based routing approach to improve lifespan in wireless body area networks Lamia Sidhoum; Mourad Hadjila; Rachid Merzougui
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.v22i2.25745

Abstract

One of the most significant limitations in wireless body area network (WBAN) is the requirement for low energy usage. For this reason, several routing techniques and protocols have been put out to provide an efficient means of energy saving during communication. In this work, we propose three approaches based on the formation of a chain of sensor nodes using a matrix of distances. The first approach is based on forming a single chain using the shortest distances. The second and the third consist in changing the position of the sink by forming a single cluster using the fuzzy C-means (FCM) method and the center of the latter constitutes the new position of the sink. In comparison to RE-ATTEMPT and PSOBAN, the third proposed chain-based approach has enabled a remarkable energy savings, which may have a big impact on the network’s entire lifespan.

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