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29,922 Article Results

Elevating cultural understanding: interactive museum exploration using 3D AR and MDLC framework

10.12928/telkomnika.v23i5.26343
Edy Jogatama; Universitas Sains dan Teknologi Komputer Purhita , Eko; Universitas Kristen Satya Wacana Sediyono , Ade; Universitas Kristen Satya Wacana Iriani
Limited access to information and interaction with artifacts in museums often hinders visitors from gaining a deeper understanding of the culture and historical context presented. This study addresses this challenge by developing a three-dimensional (3D) augmented reality (AR)-based interactive museum that enhances the museum visitor experience through an intuitive user interface (UI) and enriched content related to the exhibited artifacts. This study explores the potential of 3D AR technology in enhancing visitor engagement and interaction with museum exhibits, providing a more immersive and informative experience. This study uses the multimedia development life cycle (MDLC) as a framework to develop a 3D AR-based interactive museum. By applying the MDLC approach, this study integrates advanced AR technology with comprehensive and detailed content, resulting in a structured and user-centered interactive platform. Key benefits of this approach include enhanced interactivity, enriched artifact information, and an intuitive interface that facilitates easier access to museum content. The findings indicate that the developed interactive museum successfully overcomes the barriers of limited accessibility of information and interaction with artifacts. Through the application of advanced AR technology, the museum visitor experience is significantly enhanced, making the museum more inclusive, interactive, and educative for visitors.
Volume: 23
Issue: 5
Page: 1271-1283
Publish at: 2025-10-01

Advanced pneumonia classification using transfer learning on chest X-ray data with EfficientNet and ResNet

10.12928/telkomnika.v23i5.26387
Green Arther; Klabat University Sandag , Timothy J.; Klabat University Mulalinda , Gloria A. M.; Klabat University Susanto , Stenly R.; Klabat University Pungus
Pneumonia is a serious lung infection that demands accurate and timely diagnosis to reduce mortality. This study explores the use of deep learning and transfer learning for classifying chest X-ray images into two categories: normal and pneumonia. A total of 5,632 labeled images were used to train and evaluate six pre-trained convolutional neural network (CNN) architectures: EfficientNetB1, B3, B5, B7, ResNet50, and ResNet101. The models were tested across three training scenarios by varying learning rates (LR), batch sizes, and epochs. Among all models, EfficientNetB3 achieved the highest performance, with accuracy of 99.04%, precision of 99.76%, recall of 99.23%, and F1-score of 99.34%. These results indicate that EfficientNetB3 offers a robust and efficient solution for pneumonia detection. This research contributes to the development of intelligent diagnostic tools in the medical field and provides practical guidance for selecting effective deep learning models in clinical imaging applications.
Volume: 23
Issue: 5
Page: 1304-1313
Publish at: 2025-10-01

Gain enhanced 5.8 GHz patch antenna with defected ground structure: design and measurement

10.12928/telkomnika.v23i5.26755
Md. Nahid; Daffodil International University Hasan , Md. Sohel; Daffodil International University Rana
A rectangular microstrip patch antenna including a rectangular defective ground structure (DGS) is introduced to simultaneously enhance gain, bandwidth, and return loss while reducing antenna dimensions. This small antenna is engineered for 5.8 GHz applications, functioning throughout the frequency spectrum of 5.62 to 5.94 GHz. The design was executed on a 1.6 mm thick FR-4 substrate with a relative permittivity of 4.3, utilizing a microstrip line feed. The dimensions of the antenna are 31.75×28 ×1.6 mm³. The design approach utilized computer simulation technology (CST) Microwave Studio simulation software. The antenna attains resonance at 5.8 GHz, providing an initial bandwidth of 270 MHz and a return loss of -26 dB. A rectangular DGS was implemented to boost performance, yielding a 21.89% increase in bandwidth to 323 MHz and substantially enhancing the return loss from -23 dB to -47 dB. The gain increased from 3.95 dBi to 5.10 dBi, indicating a 30% enhancement, while sustaining an efficiency of around 83% at the resonant frequency. The antenna was constructed, and experimental measurements of parameters including gain and return loss closely matched the computer results.
Volume: 23
Issue: 5
Page: 1147-1154
Publish at: 2025-10-01

Rate-splitting multiple access in satellite-terrestrial communication systems: performance analysis

10.12928/telkomnika.v23i5.26854
Huu Q.; Industrial University of Ho Chi Minh City Tran , Khuong; Ho Chi Minh City University of Technology (HCMUT) Ho-Van
This paper investigates the throughput and outage probability (OP) of rate splitting multiple access (RSMA) in satellite–terrestrial communication networks. By dividing user messages into common and private parts, RSMA enhances spectral efficiency and user fairness while addressing hardware impairments and co-channel interference. The proposed hybrid system model is analyzed and compared with non-orthogonal multiple access (NOMA) under various power allocation coefficients and channel conditions. Results show that RSMA achieves lower OP and higher throughput than NOMA, particularly in dense multi-cell deployments. Numerical evaluations further demonstrate RSMA’s robustness against interference and hardware limitations, underscoring its potential as a reliable solution for next-generation satellite–terrestrial relay networks.
Volume: 23
Issue: 5
Page: 1137-1146
Publish at: 2025-10-01

Improved classification for imbalanced data using ensemble clustering

10.12928/telkomnika.v23i5.26897
Sharanjit; University of Delhi Kaur , Manju; University of Delhi Bhardwaj , Adi; University of Delhi Maqsood , Aditya; University of Delhi Maurya , Mayank; University of Delhi Kumar , Nishant Pratap; University of Delhi Singh
Imbalanced datasets frequently occur in fields like fraud detection and medical diagnosis, where the number of instances in the majority class vastly exceeds those in the minority class. Traditional classification algorithms often become biased towards the majority class in these scenarios. To address this challenge, we introduce a novel method called improved classification using ensemble clustering (ICEC) for imbalanced datasets in this paper. ICEC merges classification with the strengths of consensus clustering to improve the classifier’s generalization ability. This approach utilizes a cluster ensemble to capture the structural characteristics of both the majority and minority classes, and the stable clustering scheme thus delivered is used to generate new auxiliary features. These features enhance the existing feature set, helping classifiers develop a more ro bust predictive model. Extensive testing on fifteen imbalanced datasets from the knowledge extraction based on evolutionary learning (KEEL) repository demonstrates the effectiveness of our proposed method. The approach was evaluated for random forest (RF) and linear support vector machine (SVM) classifiers on these data sets. Results indicate that ICEC proved to be effective for both classifiers, with an observed F1-score improvement of more than 10% for SVM and 3%for RF.
Volume: 23
Issue: 5
Page: 1323-1332
Publish at: 2025-10-01

Improved channel quality indicator estimation using extended Kalman filter in LTE networks under diverse mobility models

10.12928/telkomnika.v23i5.27205
Hilary U.; Federal University Ezea , Mamilus A.; University of Nigeria Ahaneku , Vincent C.; University of Nigeria Chijindu , Obinna; University of Nigeria Ezeja , Udora N.; University of Nigeria Nwawelu
Accurate channel quality indicator (CQI) estimation is crucial for optimizing resource allocation, improving link adaptation, and sustaining high performance in long term evolution (LTE) networks. In real-world scenarios, where channel conditions fluctuate rapidly due to user mobility, inaccurate CQI estimation can lead to suboptimal scheduling, degraded throughput, and reduced quality of service (QoS) for both users and network operators. Traditional Kalman filter (KF) approaches often struggle with the non-linear and time-varying nature of wireless channels, especially under unpredictable mobility patterns. This paper proposes an improved CQI estimation method based on the extended Kalman filter (EKF), which models non-linear system dynamics more effectively. The method is implemented in LTE-Sim, analyzed using MATLAB, and evaluated under random and Manhattan mobility models. Results show that across mobility regimes, KF outperforms EKF in the structured Manhattan model, while in the non-linear random-direction model, EKF yields markedly higher signal-to-interference-plus-noise ratio (SINR) stability and robustness to channel variation with SINR values above 10 dB between 300-450 s and a peak of approximately 60 dB. These results underscore the importance of mobility-aware estimation strategies in enhancing LTE network adaptability and throughput.
Volume: 23
Issue: 5
Page: 1166-1176
Publish at: 2025-10-01

Experimental validation of positioning and tracking system using ultra-wideband and low-cost microcontroller units

10.12928/telkomnika.v23i5.26707
Ngoc-Son; VNU University of Engineering and Technology Duong , Minh-Tuyen; VNU University of Engineering and Technology Vu , Minh-Duc; VNU University of Engineering and Technology Nguyen , Thai-Mai Dinh; VNU University of Engineering and Technology Thi
Indoor positioning systems (IPS) have become increasingly critical in various applications, from asset tracking to smart environments. While global positioning system (GPS) offers precise outdoor localization, its signal is unavailable indoors. Ultra-wideband (UWB) technology emerges as a promising alternative due to its high accuracy, robustness against multipath interference, and ability to operate in dense environments. Aiming to develop an affordable and efficient system, we present a UWB-based IPS using the DW1000 UWB chip, evaluated with two different low-cost microcontroller units (MCUs): the ESP8266 system-on-chip (SoC) and the Arduino Uno R3. The findings suggest that the ESP8266 SoC is a superior choice for building an affordable and efficient UWB IPS, making it a compelling option for widespread adoption in budget-sensitive applications.
Volume: 23
Issue: 5
Page: 1363-1373
Publish at: 2025-10-01

Enhanced torque control for horizontal-axis wind turbines via disturbance observer assistance

10.12928/telkomnika.v23i5.26805
Edwin; Fundación Universitaria Los Libertadores Villarreal-Lopez , Horacio; Universidad de San Buenaventura Coral-Enriquez , Sergio; Samara National Research University Tamayo-Leon
This paper presents an enhanced control strategy for optimizing energy capture in horizontal axis wind turbines operating in the partial-load region (region 2). The proposed approach builds upon conventional standard torque control (STC) by incorporating a generalized extended state observer (GESO) that follows the active-disturbance-rejection paradigm. Although traditional torque control methods have proven effective under steady wind conditions, they often lack robustness against disturbances, system faults, and model uncertainties inherent in wind energy systems. The proposed observer-assisted control scheme addresses these limitations by estimating and compensating for total disturbance signals, including non-modeled dynamics, parameter uncertainties, and actuator faults. The effectiveness of the proposed control strategy is validated through comprehensive simulations using a 5 MW wind turbine model subjected to realistic operational conditions. Simulation scenarios include turbulent wind speed profiles and actuator degradation to assess controller performance. The results demonstrate improved robustness and energy capture efficiency compared to the conventional control approach, while maintaining the simplicity of the implementation. This work contributes to the development of more reliable wind energy conversion systems (WECSs) by offering a practical solution that improves both performance and fault tolerance in partial load operation.
Volume: 23
Issue: 5
Page: 1395-1403
Publish at: 2025-10-01

Enhancing computational thinking in elementary students through STEM and Mojobot

10.11591/ijere.v14i5.33091
Parinya Ruangthip , Thitichai Ruckbumrung , Wichien Rueboon
The study aims to explore the effects of using Mojobot, an interactive coding robot, within science, technology, engineering, and mathematics (STEM) education to enhance computational thinking (CT) skills among elementary school students. This research explores how educational robotics enhance algorithmic thinking, logical reasoning, and problem decomposition in young learners, addressing future workforce demands for digital literacy and problem-solving. Utilizing a quasi-experimental design with pre-test and post-test measured. The design involved a between-subject experimental group of seventy-four elementary students who were randomly assigned to an experiment (n=37) and a control group (n=37), the latter only receiving traditional STEM instruction without robotics. Students were given a pre-test and post-test to measure their algorithmic thinking, logical reasoning, and problem decomposition skills. Data were investigated using paired-samples t-tests and a 2-way analysis of variance (ANOVA). Outcomes revealed that both groups significantly improved CT skills, but the experimental group (M=28.56) improved significantly more than the control group (M=20.09) with a very large effect size (ES), respectively. The study found that a novel teaching method using Mojobot in STEM education enhances elementary students’ CT skills and supports 21st century skill development through robotics.
Volume: 14
Issue: 5
Page: 3917-3927
Publish at: 2025-10-01

Digital technology’s impact on senior high school students’ religious attitudes

10.11591/ijere.v14i5.30093
A. M. Wibowo , Nur Laili Noviani , Umi Muzayanah , Dwi Istiyani , Siti Muawanah , Mulyani Mudis Taruna , Wahab Wahab , Ahmad Muntakhib , Nugroho Eko Atmanto
The advancement of technology has revolutionized student learning, shifting from traditional textbooks to digital tools, reducing teacher-student interaction, and impacting students’ perspectives and attitudes. Students with extreme religious views sometimes rely more on digital resources than traditional ones. This study examines: i) the effect of learning resources on students’ religious attitudes; ii) the influence of social status on their attitudes; iii) the relationship between students’ motivation for religious learning and their attitudes; and iv) the interaction between diverse learning resources and social status on students’ religious attitudes. Using quantitative methods and multiple regression analysis on data from 1,020 students in Central Java, Indonesia, and employing partial least square (PLS) modeling, the study explores the influence of religious resources, social class, and motivation on students’ views. The findings show that diverse learning resources significantly foster moderate religious attitudes, with social class also playing a pivotal role. Notably, students’ motivation for religious learning mediates the relationship between learning resources and social class in shaping religious attitudes. This study contributes to educational theory by highlighting the role of learning resources in shaping outcomes, social theory by demonstrating how socioeconomic factors influence religious attitudes, and religious theory by exploring the role of digital tools in shaping religious views. These insights provide practical implications for educators in designing effective religious education strategies and promoting moderation in the digital era while emphasizing the importance of face-to-face learning for meaningful dialogue.
Volume: 14
Issue: 5
Page: 3960-3972
Publish at: 2025-10-01

Context-based learning in higher education 1992-2023: trends and outstanding research areas from Scopus database

10.11591/ijere.v14i5.33259
Hua Thi Toan , Nguyen Thi Thu Hang , Trinh Thanh Hai , Pham Nguyen Hong Ngu , Trinh Thi Phuong Thao
Context-based learning (CBL) has recently gained increasing attention as a pedagogical approach in higher education to enhance students’ understanding and problem-solving skills in real-world scenarios. This study aims to provide an overview of CBL-related issues in higher education as documented in publications from the Scopus database. A bibliometric analysis was employed to review 153 publications. The results show that articles on this topic have become more prevalent from 2009 to 2023, particularly in 2020 and 2022. A total of 443 authors from 160 institutions across 52 countries have contributed to research on this subject, with the USA being the most engaged nation in CBL studies in higher education, having the highest number of publications, citations, and research funding. The journal with the most publications on this topic is the International Journal of Science Education, classified in the Q1 category. Key research trends have been identified, focusing on applying CBL in engineering, software technology, teacher training, and nursing programs and its implementation in collaborative learning environments, distance learning, and online education. The findings are a critical resource for scholars interested in advancing research on CBL in higher education.
Volume: 14
Issue: 5
Page: 4050-4065
Publish at: 2025-10-01

Educational application of virtual reality in English education in vocational colleges: a bibliometric analysis

10.11591/ijere.v14i5.32186
Ling Yao , Mohamad Sattar Rasul , Marilssa Omar
Virtual reality (VR) technology has been widely adopted in education field for a period and its application keeps developing continuously. The bibliometric analysis was conducted to provide a comprehensive understanding of VR technology application about research strengths, research theme, scope, hot topics and evolution to enrich further study on VR technology adoption in English education in vocational colleges. The search of literature over the past decade in the Web of Science (WoS) database and 930 articles remained based on inclusion and exclusion criteria. Subsequently, VOSviewer used to analyze data from selected articles. The study finds out that research on VR technology shows an upward trend. The influential country is China, while most research institutions and authors are also from China. Research topics were identified using keyword co-occurrence analysis and four thematic clusters emerged: i) positive impact of VR on English education; ii) VR used in English education for special purpose; iii) VR is used in actual situation with the consideration of its’ features and positive effect; and iv) users’ acceptance of VR. The findings highlight current developments and offer guidance for promoting VR technology utilization in English education. Furthermore, educators could use the findings to design more effective VR-integrated curricula.
Volume: 14
Issue: 5
Page: 3812-3823
Publish at: 2025-10-01

Exploring non-education faculty’s lived teaching experiences in a Philippine higher education institution

10.11591/ijere.v14i5.33744
Julanie M. Limen , Ramil B. Arante
This qualitative, phenomenological study investigates the impact of lacking formal pedagogical training on non-education faculty in the context of Caraga State University Cabadbaran Campus (CSUCC). The research explores their lived experiences to understand the specific challenges and coping mechanisms they employ in their teaching roles. Data was collected through in-depth interviews and focus group discussions with a purposive sample of ten non-education faculty members representing various disciplines at CSUCC. The sample size of 10 participants was determined by the principle of data saturation, ensuring the collection of rich and recurring data to identify significant themes. Several key themes emerged through thematic analysis of the transcribed interviews and focus group discussions. These included self-perceived teaching efficacy, difficulties encountered in test construction and syllabus design, challenges related to student engagement, and the utilization of available resources and support systems. The findings of this study provide valuable practical implications for higher education institutions (HEIs). They suggest the necessity of implementing targeted training programs, offering relevant professional development opportunities, and establishing dedicated resources to support non-education faculty better. Ultimately, these interventions aim to enhance teaching quality, improve faculty satisfaction, and foster a more supportive teaching and learning environment.
Volume: 14
Issue: 5
Page: 3935-3945
Publish at: 2025-10-01

Advanced cloud security framework based on zero trust architecture and adaptive deep learning for next-generation systems

10.11591/ijeecs.v40.i1.pp189-201
Israa Basim , Amel Meddeb Makhlouf , Ahmed Fakhfakh
Static rule-based models and cloud access security brokers (CASBs) — traditional cloud security frameworks— can no longer effectively mitigate modern and evolving cyber threats. Two such examples include signature-based detection methods which lack real-time versatility and are ineffective against advanced persistent threats or zero-day threats. In this paper, we introduce an adaptive zero trust framework (AZTF) based on the integration of zero trust architecture (ZTA) and adaptive deep learning (ADL) approach to dynamically evaluate threats and risks being targeted on cloud environments. It continually monitors access attempts using DL models for real-time anomaly detection. Nine synthetic datasets were generated and used in the experiment in two security domains: network traffic and access pattern. The proposed system reached 96% detection accuracy, 52% improvements in response time, and 12% resource consumption optimization compared to traditional ZTA-based security models. The results highlight the power of using a combination of continuous authentication with artificial intelligence (AI)-powered dynamic security policy application to strengthen the resilience of cloud security. Future research will focus on federated learning integration, multi-cloud security applications, and explainable AI for increased transparency of models.
Volume: 40
Issue: 1
Page: 189-201
Publish at: 2025-10-01

Teaching in the digital frontier: what drives metaverse adoption in education?

10.11591/ijere.v14i5.34836
Cadelina Cassandra , Mohamad Noorman Masrek , Fadhilah Aman
The rapid evolution of digital technologies has caused dramatic changes in various areas, including education. Metaverse has become a very popular topic recently, many schools and university announce the development of metaverse, but until now there is no clear implementation of the idea and some schools cancelled to continue the implementation. One of the reasons behind it because of the lack of preparedness, reluctant from teachers, and there is no initial investigation about how the teachers will accept this technology. Several factors may influence the intention of the teachers. The purpose of this study is to analyze the factors that affect high school teachers’ intentions to use metaverse technology. By doing so, the institution can prepare for the real implementation. This study employs quantitative methods and survey techniques by developing a well-structured questionnaire from the theoretical framework. A total of 334 responses were collected and analyzed using SmartPLS software. The findings reveal that 14 hypotheses out of 18 hypotheses were significant and four others were not significant. Social influence (SI), performance expectancy (PE), effort expectancy (EE), and facilitating condition (FC) positively influence teachers’ behavioral intention (BI) to use metaverse applications. On the flip side, personal innovativeness (PI) does not significantly impact performance and EE. Trialability (TR) and corporeity (CR) also do not influence EE. However, hedonic motivation (HM), compatibility (CO), TR, interactivity (IN), and persistence are significant factors for performance and EE.
Volume: 14
Issue: 5
Page: 3601-3611
Publish at: 2025-10-01
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