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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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SELLA: An IoT-based smart shopping trolley with real-time RFID tracking and automated checkout Hadj Zerrouki; Salima Azzaz-Rahmani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 1: February 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i1.27464

Abstract

The contemporary retail sector faces a persistent challenge in enhancing in store customer experience, primarily due to inefficiencies at checkout. This paper presents smart e-cart for lean logistics application (SELLA), a smart shopping trolley system engineered to eliminate this bottleneck. The system’s architecture is centered on a Raspberry Pi 4 microcontroller, orchestrating an ultra-high frequency (UHF) radio frequency identification (RFID) subsystem for instantaneous, non-line-of-sight product identification, and a responsive 7-inch touchscreen graphical user interface (GUI) developed in PyQt. The core contribution lies in developing a self contained shopping solution with integrated payment processing, supported by comprehensive performance validation. We present a detailed methodology, including the system’s multi-threaded software architecture and core operational algorithm. Experimental evaluation demonstrates a mean tag detection accuracy of 98.2% under optimal conditions, a robust user interface (UI) latency of under 500 ms, and an average central processing unit (CPU) utilization of 28%, proving system efficiency. Comparative analysis confirms that SELLA’s integration of on-trolley automated payment and detailed performance metrics represents a significant advancement over existing prototypes. The system provides a validated, high-performance solution for next-generation smart retail environments.
The impact of software metrics in NASA metric data program dataset modules for software defect prediction Adinda Ayu Puspita Ramadhani; Radityo Adi Nugroho; Mohammad Reza Faisal; Friska Abadi; Rudy Herteno
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.v22i4.25787

Abstract

This paper discusses software metrics and their impact on software defect prediction values in the NASA metric data program (MDP) dataset. The NASA MDP dataset consists of four categories of software metrics: halstead, McCabe, LoC, and misc. However, there is no study showing which metrics participate in increasing the area under the curve (AUC) value of the NASA MDP dataset. This study utilizes 12 modules from the NASA MDP dataset, where these 12 modules are being tested into 14 relationships of software metrics derived from the four existing metric categories. Subsequently, classification is performed using the k-nearest neighbor (kNN) method. The research concludes that software metrics have a significant impact on the AUC value, with the LoC+McCabe+misc metrics relationship influencing the improvement of the AUC value. However, the metrics relationship that has the most impact on achieving less optimal AUC values is McCabe. Halstead metric also plays a role in decreasing the performance of other metrics.
SOM-SIS approach to auto summary of clustering results on university academic performance Rahayu Widayanti; Sarifuddin Madenda; Eri Prasetyo Wibowo; Khoerul Anwar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 1: February 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i1.24238

Abstract

The analysis of the performance of higher education academic quality in terms of student achievement, study period, and drop out rates is still an intensive study among researchers. Several clustering methods are often used to understand student and graduate groups, in influencing college performance. However, the conventional method has only arrived at the results of clustering, so it is difficult to interpret it as a support for academic decisions, especially in mapping the position of universities against other universities nationally. This article introduces a combination of techniques from self organizing map and technique for oorder preference by similarity to an ideal solution (SOM-SIS), an auto-summarizing technique from clustering results as well as mapping university academic performance. First, the academic performance indicators are grouped using the self organizing map (SOM) method and the results are concluded using the technique for order preference by similarity to an ideal solution (TOPSIS) approach. The SOM-SIS technique was tested using data from one of the universities in Indonesia. As a result, the SOM-SIS technique has a 100% compatibility rate with the higher education quality assurance system, through recommendations from three university experts.
Indonesian continuous speech recognition optimization with convolution bidirectional long short-term memory architecture Sukmawati Nur Endah; Rismiyati Rismiyati; Priyo Sidik Sasongko; Anwar Petrus F Noiborhu
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.v23i3.24994

Abstract

Speech recognition can be defined as converting voice signals into text or lines of words by using algorithms implemented in computer programs. There are several types of speech recognition, including recognition for isolated word speech, continuous speech, spontaneous speech, and conversational speech. Research on continuous speech recognition, especially in Indonesian, has been developed using both stochastic methods such as Hidden Markov model (HMM) and deep learning methods. Currently, deep learning approaches are more widely used in speech recognition applications. This research optimizes Indonesian speech recognition by adding convolution layers to the bidirectional long short-term memory (Bi-LSTM) architecture. The goal of this research is to find the best architecture so that better Indonesian continuous speech recognition results can be obtained. The dataset used in this research was created by the intelligent systems research group in the Department of Informatics at Universitas Diponegoro. All speakers who participated in this dataset came from five ethnic groups in Indonesia, representing the dialects of their respective ethnic groups. The research results show that by adding a convolution layer to the Bi-LSTM architecture, speech recognition performance increases significantly with an average word error rate (WER) reduction of 15.56% compared to using only the Bi-LSTM architecture.
Compact reconfigurable PIFA antenna for wireless applications Abdullah Ali Jabber; Ali Khalid Jassim; Raad Hamdan Thaher
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.v18i2.13427

Abstract

This paper presents, new compact and multiband frequency reconfigurable planar inverted-F antenna (PIFA). The antenna is designed and optimized to cover mobile application devices like GPS, WLAN/Wi-Fi, WiMAX, 4G LTE, UWB, and satellite applications. The frequency reconfigurability is obtained by using only a single RF switch (PIN diode) for changing the operating frequency. The antenna dimensions are 45.6x39.6x1.6 mm3 printed on an FR-4 epoxy substrate with relative dielectric constant εr = 4.3, loss tangent tan (δ) = 0.002 and 50 Ω coaxial feed line. The proposed antenna has two patches connected by a single PIN diode. The antenna introduces nine resonant frequencies under (S11 ≤ -10 dB) which are: 0.980 GHz, 3.392 GHz, 3.924 GHz, 4.554 GHz, 5.82 GHz, 6.81 GHz, 7.305 GHz, 8 GHz and 8.105 GHz in the ON and OFF states of the PIN diode which are applicable to cover GSM900, WLAN/Wi-Fi, WiMAX, 4G LTE, UWB, and satellite systems. The obtained maximum simulated gain is 8.45 dB at 6.81 GHz. The lowest return loss is obtained to be -42 dB at 5.854 GHz. Detailed simulation and measurement results are explored and studied in this research. The CST software is used to simulate and optimize the proposed PIFA antenna. The proposed antenna has been fabricated and produced a good agreement with the simulation results.
Evolutionary programming approach for securing medical images using genetic algorithm and standard deviation Shihab A. Shawkat; Najiba Tagougui; Monji Kherallah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 6: December 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i6.25231

Abstract

The integrity and security of medical data have become a big challenge for healthcare services applications. Images of hidden text represent steganography forms in which the image is exploited as an object to cover information and data. So, the data masking ability and image quality of the cover object are significant elements in image masking. In this study, the patient’s personal information and message generated by the doctor’s comment are stored in the images. Image pixels and message bits are exchanged sequentially. The best cluster is randomly selected using the genetic algorithm (GA) and standard deviation (STD) methods. The method, depending on optimizing and taking benefits of the similarities between pixels, has been proposed. High image quality can be achieved by using stego-image and increasing the data amount to be hidden. Analysis metrics of visual quality such as peak signal to noise ratio (PSNR), mean square error (MSE), structural similarity index measure (SSIM) and bit error rate (BER) are adopted to assess the performance of the method proposed. The suggested and proposed model has proven its capability to mask the secrete data of patients into a cover image transmitted with high ability, imperceptibility, and minimal future degradation.
Detection of image manipulation with convolutional neural network and local feature descriptors Ali Ahmad Aminu; Nwojo Nnanna Agwu; Steve Adeshina; Muhammed Kabir Ahmed
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.v20i3.23318

Abstract

In recent times, numerous digital image manipulation detection approaches have been proposed to detect which processing operations were applied to manipulate digital images. Most of these approaches consider the situation in which an image is manipulated by only one manipulation operation. However, practical image manipulation often involves multiple manipulation operations. It is important to detect multiple image manipulation operations and the order in which they were applied to establish the origin and genuineness of a given image as well as the processing history it has gone through. In this article, we proposed a new method to determine multiple image processing operation and operation chains based on convolutional neural network (CNN) and local optimal oriented pattern (LOOP). The proposed method is based on CNN and LOOP in which CNN extracts and learns image manipulation traces from the LOOP maps of the input images that are classified using softmax, extra-tree, and extreme gradient boosting (XGBOOST) classifiers. Detailed experiments show that the proposed model can attain overall detection accuracies of 99.81% and 99.15% in identifying different image manipulations and manipulation operation chains, respectively
Design of vehicle to vehicle communication: accident collision prevention using light fidelity and wireless fidelity technology Folashade Olamide Ariba; Yusuf Isaac Onimisi; Adedotun Ijagbemi; Dickson Ogochukwu Egbune
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.v24i2.27570

Abstract

Vehicle-to-vehicle (V2V) communication is a key component of intelligent transportation systems (ITS), enabling seamless data exchange between vehicles to limit collision risks. This study presents a hybrid communication framework that integrates light fidelity (LiFi) and wireless fidelity (WiFi) technologies to enhance safety and reliability in accident prevention. Lifi using visible light communication, provides line-of-sight for short-range communication, while WiFi ensures long-range coverage in dynamic traffic environments. The proposed system allows vehicles to share speed, braking, and positional data, enabling timely warnings to drivers in high-risk scenarios. The system fuses data communication protocol design, simulation, prototype development, testing, and evaluation. The prototype model was designed and simulated to evaluate the performance of the system in terms of functionality, timing and reliability. Results indicate that the hybrid LiFi-WiFi system improves data transmission efficiency and reduces delay compared to standalone wireless systems. This approach demonstrates significant potential in developing safer transportation networks by combining complementary wireless technologies for V2V communication.
Class-G series audio power amplifier for subwoofer Budihardja Murtianta; Darmawan Utomo; Atyanta Nika Rumaksari; Jae-Wook Lee
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 5: October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i5.25900

Abstract

An audio power amplifier is an electronic device used to amplify a small signal source power at the input into a large signal power at the output that is speaker. In general, audio power amplifiers use class-AB amplifiers. In the process of amplifying the signal power, there will be power losses in the amplifiers which results in relatively lower amplifier power efficiency because there is a difference between the supply and output voltage levels. In this paper a class-G series audio power amplifier for subwoofers is designed to minimize these power losses and increase the power efficiency of the amplifier. The designed amplifier voltage supply is 40 V with a maximum output power of 80 W at an 8 Ω load. The amplifier has frequency response from 20–200 Hz and gain twice. Realization of the power amplifier and measurements were carried out using the circuit maker simulator, and the measurement results of the class-G power amplifier were compared with the class-AB power amplifier. The measurement results show that both power amplifiers meet the design specifications. The proposed class-G amplifier has 0.14% larger total harmonic distortion (THD) but has 10.4% greater power efficiency advantages over the class-AB amplifier.
A survey on security and policy aspects of blockchain technology Haider Hadi Abbas; Montadher Issam Abdul Kareem; Hassan Muwafaq Gheni
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.v21i2.24738

Abstract

This survey talks about the problem of security and privacy in the blockchain ecosystem which is currently a hot issue in the blockchain community. The survey intended to study this problem by considering different types of attacks in the blockchain network with respect to algorithms presented. After a preliminary literature review it seems that some focus has been given to study the first use case while, to the best of my knowledge, the second use case requires more attention when blockchain is applied to study it. The research is also interested in exploring the link between these two use cases to study the overall data ownership preserving accountable system which will be a novel contribution of this work. However, due to the subsequent government mandated secrecy around the implementation of data encryption standard (DES), and the distrust of the academic community because of this, a movement was spawned that put a premium on individual privacy and decentralized control. This movement brought together the top minds in encryption and spawned the technology we know of as blockchain today. This survey explores the genesis of encryption, its early adoption, and the government meddling which eventually spawned a movement which gave birth to the ideas behind blockchain.

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