TELKOMNIKA (Telecommunication Computing Electronics and Control)

Journal Information
ISSN / EISSN : 1693-6930 / 2302-9293
Published by: Universitas Ahmad Dahlan (10.12928)
Total articles ≅ 2,816
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My Hanh Nguyen Thi, Phung Ton That, Nguyen Doan Quoc Anh
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 950-956; doi:10.12928/telkomnika.v19i3.15832

The poor color rendering index (CRI) induced by mono chip and phosphor configuration in the conventional white-light light-emitting diode (LED) urges for developments in both packaging and material, thus, a modern lighting solution was introduced. The dual-layer phosphor package is an innovative configuration that can retain the lumen output of conventional white light emitting diode (WLED) while also enhancing color quality. The structure of dual-layer phosphor package that was proposed includes two chips and one phosphor. The priority in this research is to keep improving the lighting properties of WLED, therefore, further experiments with this dual-chips and dual-phosphor package are conducted. The lighting properties of LED are measured multiple times with its nitride-based phosphor being altered in proportions and densities each occasion, the results are calculated with a color design model made specifically to monitor and adjust the color of white-light from LED to match desired outcome. The WLED at 5600 K correlated color temperature (CCT) is the sole research object of the experiments. The measured parameters from the 5600 K WLED and the color coordinates of CIE 1931 simulated from the color design model show that 0.0063 is the highest possible discrepancy at 5600 K (CCT). The information from this manuscript provide the manufacturers with the most efficient approach to create a white LED that has good color quality, high CRI and luminous flux.
Mohammed B. Essa, Lubna A. Alnabi, Abbas K. Dhaher
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 1039-1049; doi:10.12928/telkomnika.v19i3.15223

The population is speeding up and the demands for electrical energy are clearly increasing, this growth in load leads to higher power loss and Voltage drop. This paper is focused on a method to decrease the power losses and voltage profile improvement. The first suggested technique binary particle swarm optimization BPSO is utilized for solving the problem of the power loss minimization in network distribution. This work based on optimum position and sizing of the distribution generation (DG) units, shunt capacitor (SC) with network reconfiguration is applied to show the improvement of the network distribution efficiency. The MATLAB programming part and software package MATPOWER7 are used to simulate 69-bus and 33-bus test system with three different cases of loads and different number of DG and SC. The result showed a positive impact on system efficiency in comparison with other previous studies. This paper showed that increase of DG and capacitor does not usually give the best result although the increase of system cost, maintenance, and the units' distance for gas supplying.
Mazen M. A. Al Ibraheemi, Fatih J. Anayi, Zainb Hassan Radhy, Hayder Al Ibraheemi
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 983-990; doi:10.12928/telkomnika.v19i3.18794

Considerations around environmental pollution and green energy usage have led to environmentally-friendly machines being used in many industrial applications. Permanent magnet (PM) machines are the best solution to substitute the pollutant diesel-powered machines. In such machines, rotor position detection is crucial for safe startup operating. Meanwhile, encoderless controllers have become more reliable, over the years, in supporting the operation of PM machines. The key point, presented by this paper, is to introduce an improved positioning model to detect the rotor-position of interior permanent magnet synchronous machine at halt condition. To verify this objective, only two short duration pulses were injected into the stator windings. Then, the corresponding terminal voltage and current responses were measured and employed to create two memory address lines. Thereby, the memory cells, which contain the rotor position information, could be accessed. This detection model makes a significant improvement in rotor positioning detection of high resolution (1 degree) which represents lower value than most verified results in literature. The model was simulated and tested in a MATLAB/Simulink environment and shows an approximate accuracy 95%. Additionally, the statistical analysis was also employed to support the work outcomes.
Van Van Huynh, Phong Thanh Tran, Tuan Anh Tran, Dao Huy Tuan, Van-Duc Phan
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 1001-1009; doi:10.12928/telkomnika.v19i3.18777

In this paper, we develop a new extended state variable observer based LFC scheme for three-area interconnected power systems. The extended state observerbased load frequency controllers are developed which utilize disturbance estimation techniques. The propose control approach assures that the fluctuating things of the load frequencies reaches to a safer range and the load frequencies can also be made at a very minimal not to have an effect on power quality and power flow in multi-area interconnected power system. The results of the simulations using MATLAB/SIMULINK done did not only address that the proposed newly control method works effectively but also change powerfully the parameter variations of the interconnected areas of the power system. Especially, it works very well to limit disturbances impact on interconnected areas in the system. Therefore, the performance of interconnected power system under different multi-conditions is simulated with the new control method to demonstrate the feasibility of the system.
Fauzy Bin Che Yayah, Khairil Imran Ghauth, Choo-Yee Ting
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 872-885; doi:10.12928/telkomnika.v19i3.18159

In the big data age, extracting applicable information using traditional machine learning methodology is very challenging. This problem emerges from the restricted design of existing traditional machine learning algorithms, which do not entirely support large datasets and distributed processing. The large volume of data nowadays demands an efficient method of building machine-learning classifiers to classify big data. New research is proposed to solve problems by converting traditional machine learning classification into a parallel capable. Apache Spark is recommended as the primary data processing framework for the research activities. The dataset used in this research is related to the telco trouble ticket, identified as one of the large volume datasets. The study aims to solve the data classification problem in a single machine using traditional classifiers such as W-J48. The proposed solution is to enable a conventional classifier to execute the classification method using big data platforms such as Hadoop. This study’s significant contribution is the output matrix evaluation, such as accuracy and computational time taken from both ways resulting from hyper-parameter tuning and improvement of W-J48 classification accuracy for the telco trouble ticket dataset. Additional optimization and estimation techniques have been incorporated into the study, such as grid search and cross-validation method, which significantly improves classification accuracy by 22.62% and reduces the classification time by 21.1% in parallel execution inside the big data environment.
Hayder Fakher Jassim, Mohammed A. Tawfeeq, Sawsan M. Mahmoud
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 705-715; doi:10.12928/telkomnika.v19i3.18354

The rapid development in communications and sensors technologies make wireless sensor networks (WSNs) as essential key in several advanced applications such as internet of things (IoT). The increasing demands on using WSNs required high quality of services (QoS) because most WSNs applications have critical requirements. This work aims to offer a routing protocol to improve the QoS in WSNs, taking in consideration its ability to prolong the lifetime of the network, optimize the utilization of the limited bandwidth available, and decrease the latency that accompanies the packets transmitted to the gateway. The proposed protocol is called overlapped hierarchical cluster routing protocol (OHCRP). OHCRP is compared with the traditional routing protocols such as SPEED, and THVR. The results show that OHCRP reduces latency effectively and achieve high energy conservation, which lead to increase the network lifetime and insure network availability.
Siti Hasunah Mohammad, Nadiatulhuda Zulkifli, Sevia Mahdaliza Idrus
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 738-746; doi:10.12928/telkomnika.v19i3.18787

Next generation broadband access networks are gaining more interests from many key players in this field. The demands for longer reach and higher bandwidth are among the driving factors for such network as it can reach wider area up to 100 km, even beyond; has enhanced bandwidth capacity and transmission speed, but with low cost and energy consumption. One promising candidate is long reach passive optical network, a simplified network with reduced number of network elements, equipment interfaces, and even nodes; which leads to a significant reduction in the network’s capital expenditure and operational expenditure. Outcome of an extended reach often results in increased propagation delay of dynamic bandwidth allocation messages exchange between the optical line terminals and optical network units, leading to the degradations of bandwidth allocation and quality of service support. Therefore, an effective bandwidth allocation algorithm with appropriate service interval setup for a long reach network is proposed to ensure the delay is maintained under ITU-T G.987.1 standard requirement. An existing algorithm is improved in terms of service interval so that it can perform well beyond 100 km. Findings show that the improved algorithm can reduce the mean delay of high priority traffic classes for distance up to 140 km.
Nur Hayatin, Kharisma Muzaki Ghufron, Galih Wasis Wicaksono
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 754-761; doi:10.12928/telkomnika.v19i3.18356

Facing the news on the internet about the spreading of Corona virus disease 2019 (COVID-19) is challenging because it is required a long time to get valuable information from the news. Deep learning has a significant impact on NLP research. However, the deep learning models used in several studies, especially in document summary, still have a deficiency. For example, the maximum output of long text provides incorrectly. The other results are redundant, or the characters repeatedly appeared so that the resulting sentences were less organized, and the recall value obtained was low. This study aims to summarize using a deep learning model implemented to COVID-19 news documents. We proposed transformer as base language models with architectural modification as the basis for designing the model to improve results significantly in document summarization. We make a transformer-based architecture model with encoder and decoder that can be done several times repeatedly and make a comparison of layer modifications based on scoring. From the resulting experiment used, ROUGE-1 and ROUGE-2 show the good performance for the proposed model with scores 0.58 and 0.42, respectively, with a training time of 11438 seconds. The model proposed was evidently effective in improving result performance in abstractive document summarization.
Gilbert Christopher, Arya Wicaksana
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 762-769; doi:10.12928/telkomnika.v19i3.18792

The thesis defense timetabling problem is a fascinating and original NP-hard optimization problem. The problem involves assigning the participants to defense sessions, composing the relevant committees, satisfying the constraints, and optimizing the objectives. This study defines the problem formulation that applies to Universitas Multimedia Nusantara (UMN) and use the particle swarm optimization (PSO) algorithm to solve it. As a demonstration of concept and viability, the proposed method is implemented in a web-based platform using Python and Flask. The implementation is tested and evaluated using real-world instances. The results show that the fastest timetable generation is 0.18 seconds, and the slowest is 21.88 minutes for 25 students and 18 department members, without any violation of the hard constraints. The overall score of the EUCS evaluation for the application is 4.3 out of 6.
Aymen Fadhil Abbas, Usman Ullah Sheikh, Fahad Taha Al-Dhief, Mohd Norzali Haji Mohd
TELKOMNIKA (Telecommunication Computing Electronics and Control), Volume 19, pp 838-850; doi:10.12928/telkomnika.v19i3.12880

A crucial step in designing intelligent transport systems (ITS) is vehicle detection. The challenges of vehicle detection in urban roads arise because of camera position, background variations, occlusion, multiple foreground objects as well as vehicle pose. The current study provides a synopsis of state-of-the-art vehicle detection techniques, which are categorized according to motion and appearance-based techniques starting with frame differencing and background subtraction until feature extraction, a more complicated model in comparison. The advantages and disadvantages among the techniques are also highlighted with a conclusion as to the most accurate one for vehicle detection.
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