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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
 315   316   317   318   319 
Novel fractal geometry of 4×4 multi-input and multi-output array antenna for 6G wireless systems Karrar Shakir Muttair; Oras Ahmed Shareef; Hazeem Baqir Taher
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.v22i1.24978

Abstract

Recently, multiport multi-input and multi-output (MIMO) antenna technology has been the main focus of both manufacturers and researchers. So, their biggest challenge was to propose a small antenna that operates in broadband. We will be the primary contributors to the manufacturing process for this sort of antenna in this work, so we suggested a 4×4 MIMO antenna in a very compact size. As a result, the antenna dimensions are (W=16 mm, L=16 mm, H=1.6 mm) and it operates in millimeter bands ranging from 38 to 80 GHz, with a wide bandwidth of 42 GHz. This antenna was created using modern design principles, such as the Rubik’s cube form. According to the results, we noticed that the performance of the parameters is good, as the reflection coefficient is <10 dB for all frequencies. In addition, the isolation transmission performance between ports is <-26 dB, the envelope correlation coefficient (ECC) is <0.0000234 between all ports, and the diversity gain (DG) ranges between ports from 9.99 to 10 dB. Moreover, the percentage of the total antenna efficiency and radiation ranges from 70 to 98%, while the projected antenna gain range from 6.9 to 9.5 dB. With all these positive results, the suggested antenna has become one of the critical components in most contemporary wireless systems.
Design of traceability system models for potato chips agro-industry based on fuzzy system approach Ririn Regiana Dwi Satya; Eriyatno Eriyatno; Andes Ismayana; Marimin Marimin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 4: August 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i4.23316

Abstract

Identification of recorded information is the most important requirement for developing an effective traceability system. This paper aimed to develop an information technology (IT)-based traceability system combined with an intelligent system in potato chips agro-industry. In this paper, we present a business process in potato chips agro-industry which consists of three activities, i.e. raw materials receiving, processing, and warehousing of final products. First of all, a traceability system architecture was developed. To develop computational models, quality, food safety and environment criteria using fuzzy inference system (FIS) and adaptive neuro fuzzy inference system (ANFIS), and intelligent decision support system (IDSS) traceability model using android front end. An internal information capture point was identified for each step and corresponding traceability information to be recorded was determined. Furthermore, a prototype IDSS was developed to represent method of information modeling on products, processes, quality, and transformation at each node in potato chips agro-industry. In this study, intelligent systems have been developed for decision making in quality control good agricultural practices.
Development of a recommendation system for selecting a formula in cataract surgery Arseniy Lomakin; Anastasiya Donskaya; Alexander Zubkov
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 3: June 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i3.27580

Abstract

Accurate intraocular lens (IOL) power calculation remains a critical factor for achieving optimal refractive outcomes in cataract surgery. This study analyzes existing methods and software solutions for selecting formulas used to calculate IOL power. To solve this problem, a support medical decision-making recommendation system (SMDRS) was developed to analyze patient biometric data and predict the most suitable calculation formula. Among the evaluated machine learning approaches, the random forest (RF) algorithm demonstrated the highest stability and classification accuracy, leading to its selection as the core predictive engine. The system was validated using retrospective clinical data and evaluated in a functioning ophthalmology clinic. Performance evaluation demonstrated that the system increased the success rate of surgical outcomes in complex cases from 73.5% to 90.5%, thereby confirming its impact on improving the efficiency of optical calculations in clinical practice. By minimizing human error and standardizing decision-making, the proposed solution offers a robust tool for ensuring consistently superior surgical results.
Reducing feature dimensionality for cloud image classification using local binary patterns descriptor Thongchai Surinwarangkoon; Vinh Truong Hoang; Kittikhun Meethongjan
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.v22i6.25870

Abstract

Clouds play a crucial role in precipitation and weather prediction. Identifying and differentiating clouds accurately poses a significant challenge. In this paper, we present a novel approach that utilizes the local binary patterns (LBP) feature descriptor to extract color cloud images. We employ feature fusion to combine LBP features from the independent channels of the RGB color space. Furthermore, we apply five well-known feature selection methods, namely ReliefF, Ilfs, correlation-based feature selection (CFS), Fisher, and Lasso, to select relevant and useful features. These selected features are then fed into a support vector machine (SVM) classifier. Experimental results demonstrate that our proposed approach achieves superior performance by significantly reducing the number of features while maintaining prediction accuracy.
Developing a robust data integrity verification framework for cloud storage utilizing Boneh-Lynn-Shacham signatures Raed Abdulkareem Hasan; Mustafa M. Akawee; Enas Faek Aziz; Omar A. Hammood; Tole Sutikno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 4: August 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i4.26709

Abstract

Cloud computing (CC) is a service that allows both data storage and data accessibility on the cloud through any on-demand service and application, without incurring the costs of local data storage and upkeep expenses. On the other hand, CC providers have to make sure good security among the consumers to inspire them to use the resources on the cloud as if it were their local storage, without bothering about the data quality. Therefore, data checking in the cloud gains much importance mostly at the demand of the customers for the data integrity that a third-party auditor (TPA) can be introduced to verify the data soundness. A present investigation introduced a secure and efficient auditing solution for cloud data under the Boneh-Lynn-Shacham (BLS) public identities to keep the information secure and at the same time perform auditing securely. this study restructured the public key equation with the signature equation in our proposed system so that there is an increment in complexity while quality execution speed is maintained, and the proposed system allows dynamic data processing in terms of insert, delete and modification. From the analysis of the system, which includes security and performance, the proposed system is very effective and safe.
User stories collection via interactive chatbot to support requirements gathering Ferliana Dwitama; Andre Rusli
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.v18i2.14866

Abstract

Nowadays, software products have become an essential part of human life. To build software, developers must have a good understanding of the requirements of the software. However, software developers tend to jumpstart system construction without having a clear and detailed understanding of the requirements. The user story concept is one of the practices of the requirements elicitation. This paper aims to present the work conducted to develop an Android chatbot application to support the requirements elicitation activity in software engineering, making the work less time-consuming and structured even for users not accustomed to requirements engineering. The chatbot uses Nazief & Adriani stemming algorithm to pre-process the natural language it receives from the users and artificial mark-up language (AIML) as the knowledge base to process the bot’s responses. A preliminary acceptance test based on the technology acceptance model results in an 83.03% score for users’ behavioral intention to use.
Design and analysis of triple-bands microstrip patch nanoantenna for terahertz applications Farah H. Aziz; Jawad A. Hasan
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.v22i2.25266

Abstract

Terahertz (THz) technology is the utilization of electromagnetic waves with frequencies in the range of 0.1 to 10 terahertz. This frequency range is also known as the submillimeter range, lying between the microwave and infrared regions of the electromagnetic spectrum. Terahertz technology has numerous applications in various fields, such as communications, spectroscopy, imaging, and sensing. In communications, terahertz waves can transmit large amounts of data over short distances and potentially revolutionize wireless communication networks. Recently, scientists and researchers have been concentrating on terahertz technology as it continues to evolve. In this paper, we design and simulate a rectangular-shaped patch nanoantenna with a line-feeding technique; the proposed antenna is based on three layers: a perfect electric conductor (PEC) patch, a silicon substrate layer, and a fully PEC ground plane layer. The main aim is to study the impact of altering the nanoantenna’s parameters, including shape, size, ground plane, feed line, and patch nanostructures, on its behavior. The simulated antenna operates in triple-bands of frequrncywhich are 571.85, 715.66, and 905.05 THz. As a result, the applications of this terahertz frequency band are within the visible range.
Realization of Bernstein-Vazirani quantum algorithm in an interactive educational game David Gosal; Timothy Rudolf Tan; Yozef Tjandra; Hendrik Santoso Sugiarto
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.v23i5.26929

Abstract

Quantum algorithms are celebrated for their computational superiority over classical counterparts, yet they pose significant learning challenges for non-physics audiences. Among these, the Bernstein-Vazirani (BV) algorithm stands out for its quantum speedup by efficiently identifying a secret binary string. However, the accessibility of such algorithms remains constrained by their inherent technical complexity. To address this educational gap, this paper introduces a gamified, web-based tool that innovatively reinterprets the BV algorithm’s complex mathematical settings through an into engaging scenario of identifying broken lamps. Players assume the role of an investigator, utilizing both classical and quantum solvers to identify faulty lamps with minimal queries. By transforming the BV algorithm into an intuitive gameplay experience, the tool helps reducing technical barriers, making quantum concepts much more comprehensible for educators and students than traditional methods that demand rigorous mathematical understanding. Developed using Qiskit, IBM’s Python package for quantum computation, and deployed via Flask, a popular Python microframework for building web applications, the game effectively simplifies complex quantum algorithms while demonstrating the practical applications of quantum speedup. This contribution advances quantum education by merging technical depth with interactive design, fostering a broader understanding of quantum principles and inspiring new innovations in gamified learning.
Bandwidth enhanced deltoid leaf fractal antenna for 5.8 GHz WLAN applications Rani Rudrama Kodali; Polepalli Siddaiah; Mahendra Nanjappa Giri Prasad
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.v20i5.23489

Abstract

A wideband deltoid leaf fractal antenna is proposed for 5.8 GHz commonly used in industrial scientific and medical (ISM) and wireless local area networks (WLAN) applications. A microstrip patch antennas is designed with leaf shape radiating element. Using a leaf shape, it is possible to increase the perimeter of a design and thus reduce the overall dimensions of the antenna. A circular ring slot is made on the leaf shaped radiator, in a way that a circular disc is loaded at centre. Triangular fractal slots are made inside the circular disc to make it miniaturized. A partial ground is maintained with slot at centre. The antenna is fed by micro-strip feed. The locality and measurements of the fractal slots are varied to make the antenna radiate at 5.8 GHz with wider bandwidth (BW) of (2.26 GHz). The complete size of the antenna is 40 mm3 × 40 mm3 × 1.6 mm3. The step-by-step implementation of the antenna and the effects of its dimensions are compared and presented using the reflection coefficient curve. The measured reflections coefficient |S11|<-10 dB maintained the operational band from (5.36 GHz - 7.62 GHz), with gain 4.2 dBi. The proposed antenna is planned and simulated using high frequency structure simulator (HFSS). The simulated and measured comparison showed good agreement, the designed antenna is suitable for 5.8 GHz WLAN applications with wider bandwidth requirements.
Real-time anomaly detection system using best performed machine learning model Victor Mathebula; Bukohwo Michael Esiefarienrhe
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.v24i4.27561

Abstract

Effective anomaly detection is critical for protecting organizational networks against increasingly sophisticated cyber threats. However, most machine learning-based intrusion detection models are developed and validated using public benchmark datasets, which may not reflect the operational characteristics, traffic behavior, and threat patterns of real institutional networks. In the case of Umalusi, there is currently no anomaly detection model customized and validated using Umalusi-specific network traffic, creating a practical gap in deployable cybersecurity capability. This study proposes a hybrid machine learning framework tailored to support accurate, efficient, and operationally relevant anomaly detection. Using knowledge discovery in databases (KDD) process, network traffic data were collected and pre-processed through normalization, label encoding, missing value treatment, and dimensionality reduction using principal component analysis (PCA). The 16 hybrid models integrating unsupervised anomaly detection with supervised classification were implemented and comparatively evaluated. Experimental findings indicate that the density-based spatial clustering of applications databasescan (DBSCAN) + random forest (RF) model achieved 99.92% accuracy while maintaining a low false positive (FP) cost, making it suitable for a security operations centre (SOC). In addition, a Flask-based web application was developed to enable real-time deployment by sniffing live network traffic, executing inference, and persisting results in an SQLite database.

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