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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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Beyond reductionism: systems thinking for the next generation of electrical and computer engineering Tole Sutikno
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.v24i4.3776

Abstract

Classical electrical and computer engineering has achieved remarkable progress through reductionist methodologies that decompose complex systems into manageable, analyzable, and optimizable components. While this paradigm remains indispensable for scientific rigor and engineering design, it is increasingly challenged by contemporary systems characterized by interconnectedness, dynamic interactions, and multi-scale complexity. This editorial argues that future engineering requires extending, rather than replacing, reductionist thinking with systems thinking capable of capturing interdependence, emergence, resilience, and holistic system behaviour. Beyond component-level optimization, engineering must increasingly consider interactions among technological, human, environmental, and societal dimensions that collectively shape system performance and long term sustainability. Systems thinking therefore provides a complementary paradigm for understanding how complex engineering systems adapt, evolve, and generate behaviours that cannot be inferred solely from individual subsystems. This perspective redefines electrical and computer engineering as an integrated socio-technical discipline in which analytical precision is combined with systemic understanding to address increasingly complex real-world challenges. Moving beyond reductionism does not diminish the value of analytical methods but expands their scope within broader interconnected contexts. This paradigm shift establishes the conceptual foundation for the subsequent evolution toward adaptive, human centred, and ultimately responsible engineering.
The game model of investing in the academic cloud Bakhytzhan Akhmetov; Valery Lakhno; Nurzhamal Oshanova; Volodimir Malyukov; Zhuldyz Alimseitova; Aliza Turgnbayeva; Inna Malyukova; Miroslav Lakhno
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.v22i6.26121

Abstract

The article analyzes approaches to the use of cloud technologies in the process of teaching students at large universities. The model of the academic cloud of a modern university is considered. Examples of software and functional platforms that meet the needs of students in electronic learning resources are given. The deployment models of the cloud-oriented educational environment that includes private cloud infrastructure as a service (IaaS) and platform as a university service are analyzed. The cost of deploying an academic cloud based on the educational institution’s infrastructure and renting infrastructure from a vendor is compared. A multifactorial model for evaluating investment options in the university cloud in the context of fuzzy information is proposed. In contrast to the known approaches to solving such a problem, our model assumes that the dynamics of the financial states of the players are set through a system of discrete equations. These equations describe the dynamics of multidimensional variables. The latter made it possible to consider the general problem of investing in the academic cloud within the framework of a game scheme for tasks in a fuzzy formulation, with the financial resources available to the educational institution. Preference sets and optimal financial allocation strategies for building an academic cloud are found.
Customer segmentation with RFM models and demographic variable using DBSCAN algorithm Siti Monalisa; Yosie Juniarti; Eki Saputra; Fitriani Muttakin; Tengku Khairil Ahsyar
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.v21i4.22759

Abstract

The aims of this research was to identify prospective customers by conducting customer segmentation based on recency, frequency, monetary (RFM) values and demographic variables. The step were selected the data and normalized. The normalized data were clustered using the density based spatial clustering of applications with noise (DBSCAN) algorithm. The k-dist graph was utilized with RStudio tools to identify the best values for epsilon and MinPts. The outcome of utilizing epsilon 0.06 and MinPts 3 was the identification of 5 clusters and 31 data points considered as noise, resulting in a silhouette index (SI) value of 0.4222. Based on the average RFM values, cluster 1 was categorized as prospective customers, while clusters 2, 3, 4, and 5 were designated as loyal customers. Furthermore, according to demographic analysis, the majority of customers are between the ages of 35 to 45, female, married, and housewives. Women, groceries, such as rice and cooking oil, were the most popular products. Besides, the customers were mostly lecturers and lived in Pekanbaru. This was compatible with the customer target of people from upper middle class, such as lecturers, and with the location of the mart as well, which was near a campus.
Design of multiple-input and multiple-output antenna for modern wireless applications Karrar Shakir Muttair; Oras Ahmed Shareef; Ahmed Mohammed Ahmed Sabaawi; Mahmood Farhan Mosleh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 1: February 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i1.19355

Abstract

In this paper, multiple-input and multiple-output (MIMO) antennas are designed and simulated. The designed antennas are compact double-sided printed microstrip patch antennas and fed by a microstrip line. These antennas are designed for 3.5 to 10 GHz frequencies used for medical, industrial, sciences, and various fields of 5G communications and networking applications. Furthermore, a MIMO system is designed using the polarization variability of the individual antennas, which yields better results in terms of mutual coupling (S12 and S21), reflection coefficient (S11 and S22), and voltage standing wave ratio (VSWR), which is less than 2 indicate improved matching conditions. The designed antennas showed an acceptable gain (around 2 dB) and an envelope correlation coefficient (ECC) is <0.002. In addition, the proposed MIMO antennas exhibited isolation is -25 dB at 6 GHz, which is preferable in 5G mobile antennas.
A hybrid ARIMA and DNN approach with residual learning for electric vehicle charging demand forecasting Wahyu Cesar; Dwidharma Priyasta; Prasetyo Aji; Melyana Melyana; Agus Suprianto; Osen Fili Nami; Riza Riza
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.v23i6.27219

Abstract

The rapid growth of electric vehicle (EV) adoption has created significant challenges for power grid management and charging infrastructure planning. Accurate forecasting of EV charging demand is therefore essential to ensure reliable electricity supply and effective station deployment. This study proposes a novel hybrid forecasting framework that combines autoregressive integrated moving average (ARIMA) with deep neural networks (DNN) through a residual learning strategy. In this approach, ARIMA models the linear temporal patterns, while DNN captures the nonlinear residuals, resulting in improved efficiency and predictive accuracy. The proposed hybrid model is one of the first applications of the residual learning approach for EV demand forecasting in Indonesia. Experimental evaluation using real-world daily consumption data shows that the hybrid method achieved the highest prediction accuracy of 98.22%, consistently outperforming single-model baselines. Beyond technical performance, the model can support stakeholders in planning charging infrastructure and help maintain grid stability in rapidly growing EV ecosystems.
Consistency, local stability, and approximation of Shapash explanation Tsehay Admassu Assegie; Bommy Manivannan; Komal Kumar Napa; Bindu Kolappa Pillai Vijayammal; Rajkumar Govindarajan; Sangeetha Murugan; Atinkut Molla Mekonnen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 3: June 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i3.25560

Abstract

Consistency, scalability, and local stability properties ensure that a model or method produces reliable and predictable outcomes. The Shapash helps users understand how the model makes its decisions. With machine learning (ML) system, healthcare experts can identify individuals at higher risk and implement interventions to reduce the occurrence and severity of disease. ML had achieved higher prediction accuracy even though the accuracy of their prediction depends on the quality and quantity of the data used for training. Despite the wider application and higher accuracy of different ML for disease prediction, the explanation of their predictive outcome is much more important to the healthcare professional, the patient, and even their developers. However, most of the ML systems do not explain their outcomes. To address the explainability issue various techniques such as local model agnostic explanation (LIME), and shapley additive explanation (SHAP) have been proposed over the recent years. Furthermore, the consistency, local stability, and approximation of the explanation remained one of the research topics in ML. This study investigated the consistency, stability, and approximation of LIME and SHAP in predicting heart disease (HD). The result suggested that LIME and SHAP generated a similar explanation (distance=0.35), compared to the active coalition of variable (ACV) explanation (distance=0.43).
Development and design of wearable textile antenna on various fabric substrate for unlicensed ultra-wideband applications Nor Hadzfizah Mohd Radi; Mohd Muzafar Ismail; Zahriladha Zakaria; Jeefferie Abd Razak; Siti Nur Illia Abdullah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 6: December 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i6.23356

Abstract

In the area of wearable technology an enhancement of basic microstrip antenna is evolution of wearable textile antenna. A major requirement for wearable textile antenna is its flexible designed materials which incoprates of fabric in the structure. The parameters obtained from the wearable textile antenna are return loss (S-11), directivity, gain, voltage standing wave ratio (VSWR) as well as the specific absorption rate (SAR) value. All these parameters are mostly influenced by the value of substrate dielectric constant and its thickness. In this paper, the design of wearable dual band frequency microstrip antenna is presented for wireless communication services. When the federal communication commission (FSS) has allowed the operation of unlicensed ultra-wideband (UWB) thus it attracted research interest in realizing UWB antennas for wireless applications. The operating frequency of the proposed antenna ranges from 2.85 GHz to 7.3 GHz. For body-worn and wearable applications, the antenna is embedded on selected textiles (i.e. felt, denim, polyester and leather). The prorposed microstrip antenna is designed, simulated and analysed in computer simulation technology (CST) microwave studio.
Beyond coal: optimization of hybrid floating PV–hydropower systems for Indonesia’s decarbonization Firsta Zukhrufiana Setiawati; Tania June; Muh Taufik; Rudi Kurnianto
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.v24i4.27858

Abstract

Indonesia’s failure to meet the 23% renewable energy target, resulting in continued reliance on fossil fuels, necessitated a multi-criteria evaluation of hybrid energy systems. This study aimed to simultaneously minimize the levelized cost of energy (LCOE), reduce carbon dioxide (CO2) emissions (decarbonization), and maximize the renewable energy penetration by integrating a coal-fired power plant (coal), hydroelectric power plant (hydro), and floating photovoltaic (FPV) power plant at sites in western Java (West Java and Banten provinces). Thirteen configurations were evaluated using European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 climate data (1991-2020) and hybrid optimization of multiple energy resources professional (HOMER Pro) simulations. The optimal coal hydro-FPV-Li-Ion hybrid configuration achieved 91.1% renewable energy penetration, 94.5% decarbonization, avoided ~4.1 million kg CO2 annually, delivered an LCOE of $0.1201/kWh with an internal rate of return (IRR) of 7.6%, return on investment (ROI) of 5.9%, and payback period of 8.7 years. This configuration outperformed the pumped hydro storage alternative, demonstrating 38% lower capital expenditure (CAPEX) and 49% faster payback period, confirming its economic suitability for Indonesia’s fiscal constraints. These findings indicate that a hybrid energy system with battery storage technology is a technically and economically viable pathway toward Indonesia’s decarbonization agenda.
Predicting big data analytics adoption intention among small and medium enterprises in the Philippines Victor James C. Escolano; Wei-Jung Shiang; Alexander A. Hernandez; Darrel A. Cardaña
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.v23i1.26497

Abstract

Big data analytics (BDA) has increasingly become popular both in theory and practice in recent years. Globally, larger businesses have used BDA to collect, study, and evaluate vast volumes of data to identify market trends and insights that lead to sound and intelligent business decisions. However, its adoption in small and medium enterprises (SMEs) is not fully maximized because of a variety of factors, including a lack of expertise and financial repercussions. As such, this paper seeks to delve into the predictors of BDA adoption intention among SMEs in a developing nation by extending the technology acceptance model (TAM). The quantitative surveys obtained from 438 SMEs were analyzed using partial least squares and structural equation modeling (PLS-SEM). The results revealed that perceived benefits, namely system quality, information quality, and predictive analytics accuracy, had positive relationships with perceived ease of use and usefulness, subsequently leading to attitude towards using BDA. Likewise, perceived security significantly influences perceived benefits, perceived ease of use, and attitude towards use of BDA. Further, attitude towards use was the most significant predictor of intention to adopt BDA among SMEs. Generally, the study indicates a positive interest in adopting BDA among Philippine SMEs.
Economic Dispatch Thermal Generator Using Modified Improved Particle Swarm Optimization Andi Muhammad Ilyas; M. Natsir Rahman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 3: September 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i3.824

Abstract

Fuel cost of a thermal generator is its own load functions. In this research, Modified Improved Particle Swarm Optimization (MIPSO) is applied to calculate economic dispatch. Constriction Factor Approach (CFA) is used to modify IPSO algorithm because of the advantage to improve the ability of global searching and to avoid local minimum, so that the time needed to converge become faster. Simulation results achieved by using  MIPSO method at the time of peak load of of 9602 MW, obtained generation cost is Rp 7,366,912,798,34 per hour, while generation cost of real system is Rp. 7,724,012,070.30 per hour. From the simulation result can be concluded that MIPSO can reduce the generation cost of  500 kV Jawa Bali transmission system of Rp 357,099,271.96 per hour or equal to 4,64%.

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