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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
 331   332   333   334   335 
Philosophy design of single-trait based multi-feature biometric system Rabab A. Rasool; Muthana Hamd
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.v22i1.25417

Abstract

This paper presents new techniques for designing a simple and reliable multifeatured biometric system based on a single trait source. First, a one-to-one relationship between the feature’s edge and its associated angle is utilized after extracting the contrast feature using the gray-level co-occurring matrix (GLCM) method. Secondly, the classifying stage is modified to process one-dimensional vectors rather than the whole feature’s template. That means whatever the template size is, the matching operation is always processing a one-dimensional vector called a mean-feature vector which requires low storage and less computation complexity. Finally, for comparison purposes, the performances of the three biometric systems are calculated for recognizing 170 subjects taken from four facial databases. These comparisons are made using three error distance measurements. The recognition rates of the angle-based feature were very competitive to the regular edge-based results; however, the overall recognition accuracy is highly improved after fusing the decision of the two unibiometric systems using the Logic-OR operator. The fused system performance was satisfactory and it shows that the decision fusion of the single source trait based multifeatured system has promising performance represented by accuracy improvement, low storage, and low matching time.
Fast channel selection method using modified camel travelling behavior algorithm Zaineb M. Alhakeem; Ramzy S. Ali
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 3: June 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i3.24254

Abstract

Brain computer interface (BCI) is a protocol to communicate between the human brain and a device or application using brain signals. These signals translated to useful commands by using features extraction and classification. The most widely used features is the power of alpha and beta rhythms. This type of features gives only 70% of classification accuracy without any extra processing using fixed channels to read the signals. Because the distribution of the power in the brain is not a standard for all people, each one has his own brain power map. A selection algorithm is used to find the best channels that could generate higher power than the fixed ones. Modified camel travelling behavior algorithm is used to select the channels that used to extract the power of alpha and beta bands of motor imagery signals. This algorithm is faster to find the best set of channels, and obtain classification accuracy more than 95% using support vector machine classifier.
Lexicon-based comparison for suicide sentiment analysis on Twitter (X) Munawar Munawar; Dwi Sartika; Fathinatul Husnah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 5: October 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i5.25711

Abstract

Suicidal individuals frequently share their desires on social media. As a result, it was determined that a learning machine for early detection of suicide issues on social media was required. This study aims to examine Twitter (X) users’ suicide-related sentiment expressions. The results of searching X for the keywords ‘suicide’, ‘wish to die’, and ‘want to commit suicide’ for 4 months yielded 5,535 tweets. Following the cleaning process, 2,425 tweets were collected. The findings of labeling with the lexicon-based valence aware dictionary and sentiment reasoner (VADER) and Indonesia sentiment (INSET) lexicon, which psychologists confirmed, revealed that VADER was more accurate (92.1%) than INSET (81.6%). Sentiment research reveals negative (86.4%), positive (11.1%), and neutral (2.5%) sentiment. Support vector machine (SVM), K-nearest neighbor (KNN), and Naïve Bayes modeling results show accuracy above 86%, with SVM having the best accuracy (87.65%). Because of its great accuracy, this model can be used to identify and analyze suspicious behavior relating to suicide on X. Further research is still required, despite the excellent identification of early indicators of suicide ideation from social media posts.
An improved electricity efficiency method based on microcontroller and IoT with infrared sensor Arif Ainur Rafiq; Sugeng Dwi Riyanto; Ratna Wardani
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.v18i2.14889

Abstract

This paper proposes an improved electricity efficiency method using an infrared sensor and internet of things (IoT). Almost all field of human work require electrical energy, especially for household needs. The averages household has many lamps in each room, so if it is not controlled, it will be wasteful of energy. However, this work is carried out to gain a better understanding of a new method for saving energy. The main advantage of this work is the simplification of the sensor used, in which only the infrared sensor required. Although the proposed approach faces numerous challenges, it successfully provides result as parameters that it can be processed rapidly using low-cost microcontrollers. The idea is based on the microcontroller and internet implementation with infrared sensor to monitor the number of people in home to control the lamp light intensity. The idea is proven in two ways: design and experiment. In this paper, the implementation of Raspberry Pi and Arduino is created to monitor the number of people in room and control the lamp intensity through internet or web. Arduino uses for the sensor processing and Raspberry Pi as server. The web is used to display the monitoring result by retrieving data from database that created using MySQL. The result indicates that the electricity bill decreased between 7.7-8.2% over 2 months implementation. The conclusion of this study suggests that the research in this area could be directed toward to be used in saving electricity usage in human life, especially for household.
Sand cat swarm optimization for controlling PID in DC motor Widi Aribowo; Ehab Saif Ghith; Reza Rahmadian; Mahendra Widyartono; Ayusta Lukita Wardani; Aditya Prapanca; Nur Vidia Laksmi B.
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.v22i2.25630

Abstract

In this article, the direct current (DC) motor control approach is presented using the sand cat swarm optimization (SCSO) method to obtain the best proportional integral derivative (PID) parameters. DC motors are popular equipment. In addition, DC motors are easy to apply. SCSO is a method that adopts the desert cat’s life in nature when searching for prey. This cat is able to detect low frequencies below 2 kHz and also has an extraordinary ability to dig for prey. This research was carried out using the MATLAB/Simulink application. To obtain the performance of the SCSO method, a comparison method was used, namely particle swarm optimization (PSO), gray wolf optimizer (GWO), whale optimization algorithm (WOA), and aquila optimizer (AO). From the results of the study, it was found that the settling time value and integral total weighted absolute value error (ITAE) value of the SCSO method were the best compared to other methods.
Optimizing vehicle inspection efficiency and integrity in Tanzania through blockchain technology Cleverence Kombe; Robert Sikumbili; Leticia Mihayo; Angela- Aida Runyoro
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.v23i6.26913

Abstract

This study proposes a blockchain-based solution to improve the efficiency and integrity of vehicle inspections in Tanzania, with a focus on the National Institute of Transport. The system combines Hyperledger fabric, a permissioned blockchain that provides identity management and fine-grained access control, with the InterPlanetary file system (IPFS), a decentralized content-addressed store for large artifacts such as inspection images and portable document format (PDF) forms. Smart contracts encode inspection rules and approvals, which yield tamper-evident records, faster retrieval of histories, and uniform enforcement across centers. A mathematical model based on the M/M/1 queueing system, combined with a cost-benefit analysis, supports empirical findings: the total inspection cycle time decreases by approximately 30 percent, the average waiting time declines by about 20 to 30 percent, and annual operational savings reach approximately USD 800,000. These gains enhance auditability and transparency, which contribute to road safety outcomes by reducing opportunities for tampering and error. The design includes offline capture with later synchronization, which suits centers with intermittent connectivity. The approach is transferable to adjacent public services, for example, licensing, fine collection, and selected registries.
Clutter reduction technique based on clutter model for automatic target classification in forward scatter radar Nur Emileen Abd Rashid; Nor Ayu Zalina Zakaria; Zuhani Ismail Khan; Siti Amalina Enche Ab Rahim; Nur Luqman Saleh
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.v20i5.24090

Abstract

Classification becomes one of the important elements in the forward scatter radar (FSR) micro-sensors network. This classification performance is dependent on the target’s profile behaviour and the network’s surrounding; and one of the factors that cause the reduction of classification probability is the presence of ground clutter. As the volume of clutter increases, their masking effect becomes greater and may result in more significant errors in target classification. Hence, to reduce misclassification in the FSR sensor network, a new clutter reduction technique based on the ground clutter model is proposed. Simulated ground clutter is modeled based on the estimated signal to clutter ratio (SCR) of the received signal. The clutter effect is diminished by eliminating simulated like-clutter from the receiving signals. The result shows improvement in the classification accuracy, especially for the minimum value of the SCR and this new technique uses only one database which will shorten the processing time and reduce the overall database’s size.
A vector-valued PDE model unifying anisotropic diffusion and shock filter for color images denoising and deblurring Said Karoui; Salim Bettahar
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.v24i4.27726

Abstract

This paper proposes a novel and efficient method for the restoration of color images degraded by the combined effects of noise and blur. To address this challenging inverse problem, a mixed partial differential equation (PDE) model based on a semi-implicit numerical scheme is developed for color image restoration. The proposed approach integrates anisotropic diffusion and shock filtering within a unified vector-valued framework, allowing the different color channels to be processed jointly while preserving their mutual correlation. This formulation enables selective smoothing that efficiently suppresses noise in homogeneous regions while simultaneously enhancing and preserving significant edge and structural features. Extensive experimental results on various color images demonstrate that the proposed method consistently outperforms existing color image restoration techniques. Quantitative evaluations based on standard image quality assessment metrics, including peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), confirm the superior restoration performance of the proposed approach. Furthermore, the proposed model maintains chromatic consistency across color channels during simultaneous denoising and deblurring, effectively preventing the introduction of color artifacts and ensuring visually faithful restoration results. The numerical implementation of the proposed method is based on a semi-implicit scheme.
BER performance in NOMA downlink transmission using AWGN, Rayleigh, and Rician fading channels Abdelbari Falloun; Abdessalam Ait Madi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 1: February 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i1.26050

Abstract

5G wireless technology is accessible to a much larger user base compared to previous cellular networks. Users can connect to base stations (BSs) in a variety of methods, including of frequency division multiplexing (FDM), orthogonal frequency division multiplexing (OFDM), orthogonal multiple access (OMA), and non-orthogonal multiple access (NOMA). NOMA is considered to be the best one for 5G. Additionally, NOMA employs radio resource optimization and interference control techniques to enhance spectrum network efficiency and support extremely large connections, such as successive interference cancellation (SIC). Users can be divided into two categories: strong and weak. While weak users may experience a low data rate, strong users need a high one. In this paper, we examine the two users in relation to transmit power, the indicative bit error rate (BER), outage probability (OP), and rate attainable capacity using additive white gaussian noise (AWGN) channel. Moreover, we compare the BER and signal-to-noise ratio (SNR) per bit for two users, showing that the Rician fading channel performs better than the Rayleigh fading channel. The use of NOMA technology is the optimal choice and indicates an improvement in the precision of data transmission within the communication system, particularly in the presence of noise and interference.
Estimating losses at 40-GHz downlink using non-meteorological techniques in heavy rain areas Nur Hanis Sabrina Suhaimi; Ahmad Fadzil Ismail; Yasser Asrul Ahmad; Khairayu Badron
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.v21i4.24711

Abstract

The advancement of satellite communication has arisen tremendously where higher capacity communications systems are needed. Most satellite engineers are shifting to Ka, Q, and V-band upcoming since the low frequencies such as below 10 GHz are already congested. Actual measurement data at millimetre-wave frequencies in tropical regions are minimal. The prediction of rain attenuation at frequencies above 10 GHz is required to determine a reliable fade margin. In this paper, a statistical frequency scaling technique has been developed as an alternative way of estimating rain attenuation. The technique was derived based on the correlation between the attenuation ratio of a higher and lower frequency against the attenuation at a lower frequency. The attenuations from the proposed model were compared to the proposed frequency scaling by International Telecommunication Union-R (ITU-R) as well as the conventional ITU-R rain prediction model. To deliver a reliable model, validation methods have been done using a set of data with different years and locations in tropical regions. A dependent prediction technique with the lowest root mean square error (RMSE) value and error was produced. This technique is beneficial in applying suitable mitigation techniques to moderate rain fade in tropical regions.

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