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31,456 Article Results

Emotional profile of learners in self-isolation period

10.11591/ijere.v14i4.33006
Zhanargul Kurmangaliyeva , Karakat Nagymzhanova , Serik Zhantikeyev , Almat Nuradinov
The purpose of the study was to identify the main factors affecting the emotional state of students in self-isolation. The study was carried out surveys of students of L.N. Gumilyov Eurasian National University. As a result of the study, it was found that the COVID-19 pandemic significantly affected students, causing them stress, anxiety and loneliness due to forced self-isolation and transition to distance learning. The study found that strong family relationships, friend support, and lecturer attention positively impacted students’ stress levels, loneliness, and emotional well-being. The conducted study also revealed that learning factors such as study load, ways of learning and degree of self-efficacy play an important role in students’ emotional well-being. A survey of students revealed that they used various methods of emotional self-regulation such as meditation, breathing exercises, sports and creative activities.
Volume: 14
Issue: 4
Page: 3193-3200
Publish at: 2025-08-01

Development of mobile-based Batak script recognition application using YOLOv8 algorithm

10.11591/ijeecs.v39.i2.pp1013-1026
Iustisia Natalia Simbolon , Herimanto Herimanto , Ranty Deviana Siahaan , Samuel Adika Lumbantobing , Grace Natalia Br Sitepu
The Batak people are one of the ethnic groups that pass down many values and traditions to each generation, including the written tradition known as the Batak script. The Batak Toba people, in particular, have the Batak Toba script as part of their local wisdom that needs to be preserved and maintained. However, the use of the Batak script has significantly declined in the current era. To prevent the loss of this heritage, preservation through technology is necessary. This research utilizes a deep learning approach using the YOLOv8 algorithm to detect images of script objects, provide the coordinates of the script locations, and perform object recognition based on the dataset. The final result of this research is an Android-based application that can detect the Batak Toba script in real time and upload images. The research process involves experiments on several hyperparameters, such as epochs with a value of 200, confidence threshold, and IoU with a value of 0.5. The model evaluation shows excellent results, with a precision of 0.945, recall of 0.902, mAP@0.5 of 0.954, and a high confidence score from the application's detection.
Volume: 39
Issue: 2
Page: 1013-1026
Publish at: 2025-08-01

Technology of adaptive physical education for children aged 7-9 years with autism spectrum disorder

10.11591/ijere.v14i4.33185
Tulegen Botagariyev , Svetlana Кubiyeva , Nurolla Mambetov , Alpysbay Aralbayev , Amangazy Syzdykov , Saniya Konisbaeva
Analysis of the scientific and methodological literature indicates that the issue of scientific and methodological support for children with autism spectrum disorder (ASD) is insufficiently addressed, particularly for the age group of 7-9 years, which is the focus of this study. The aim of the research is to develop and empirically demonstrate a method for adaptive physical education for children with autism aged 7-9 years. The study involved 20 children attending a neurological rehabilitation center and a general education school. The methodology included the use of paired t-tests to compare indicators before and after the intervention. Key findings included significant improvements in physical indicators such as lung vital capacity (LVC), hand strength, and motor coordination. The practical significance of this research lies in the development of an effective adaptive physical education program that can be implemented in educational and rehabilitation institutions to support children with ASD. Future research prospects include increasing the sample size and conducting long-term observations to examine the sustainability of the obtained results.
Volume: 14
Issue: 4
Page: 2921-2930
Publish at: 2025-08-01

English learning perceptions and career implications: insights from tertiary-level students

10.11591/ijere.v14i4.32836
Samia A. Abu El-Haj , Hala Abu El-Haj , Nadia Mustafa Al-Assaf
This study investigates students’ perceptions of English language learning at the tertiary level, focusing on its importance for academic success and future career opportunities. The problem addressed is the gap in understanding how students perceive the relevance of English proficiency to their professional futures and the challenges they face in achieving proficiency. A descriptive-analytical and correlational research design was employed, using data from 127 students across various majors and years of study at the University of Jordan, with 122 valid responses. The research utilized a structured questionnaire to explore students’ learning goals, perceived importance of English proficiency, and the challenges they face in language classes. Statistical analysis was applied to identify significant relationships between variables. The major findings reveal that students view English proficiency, particularly in speaking, as critical for their professional futures. However, challenges such as inadequate classroom resources and limited opportunities for practice were commonly reported. The proposed solution emphasizes the need for enhanced language instruction that aligns with students’ professional goals, alongside improvements in classroom infrastructure and more practical language engagement opportunities. The study concludes that addressing these challenges could significantly improve students’ English learning outcomes and better prepare them for their future careers.
Volume: 14
Issue: 4
Page: 3325-3335
Publish at: 2025-08-01

Exploring school resilience in the context of globalizing digital change: the impact on teacher management

10.11591/ijere.v14i4.29697
Asma Khaleel Abdallah , Guzalia Shagivaleeva , Elena Kolomoets
Administrators in educational institutions will need to implement smart and well-designed changes in teacher management to mitigate the negative effects. Using teacher resilience as an example, the study seeks to assess the level of resilience in schools and analyze its effects on teacher management. The study includes 197 teachers from 31 Russian schools in Kazan, Elabuga, Moscow, and Yekaterinburg, and 100 foreign teachers working in United Arab Emirates. The research design was descriptive transactional and based on a questionnaire. The study yielded the following findings: i) 89.4% of teachers have a high level of stress, 94.2% have a high level of worry, 92.3% have a high level of anxiety, 33.8% have a low level of resilience, and 95.7% were in a difficult emotional state and ii) the inquiry-based stress reduction (IBSR) practice had a positive effect on increasing teacher resilience. This indicated that implementing such changes in teacher management might be successful in boosting teacher resilience, which would affect school resilience generally. Educational researchers have confirmed the effectiveness of the IBSR tool in boosting teacher resiliency, and the results of this study can aid school administrators in developing new management models utilizing this tool.
Volume: 14
Issue: 4
Page: 3078-3088
Publish at: 2025-08-01

Work-integrated curriculum transformation and autopedagogical competence in prospective teachers

10.11591/ijere.v14i4.33746
Aiym Tynyskhanova , Kalbike Yessenova , Irodakhon Xoldarova , Fariza Ismailova , Aziza Zhunusbekova
Despite substantial investments in higher education, many Kazakhstani graduates face challenges in securing employment due to a lack of essential job-related competencies. The predominant discipline-based learning approach in Kazakhstani universities often fails to cultivate autopedagogical competence—a critical skill for applying knowledge in real-world contexts and solving practical problems. This study aims to examine the impact of work-integrated curriculum (WIC) transformation on the development of student autopedagogical competence (SAC). A non-experimental quantitative research design was employed, utilizing survey techniques to collect data from a sample of 180 students in Kazakhstan. The sample was determined through random stratified sampling to ensure representativeness. Data analysis was conducted using structural equation modeling (SEM) to identify relationships between dependent (autopedagogical competence), independent (WIC transformation), and moderating variables. The findings reveal that curriculum transformation has a significant and positive impact on the development of autopedagogical competencies. Students exposed to work-integrated learning (WIL) demonstrate stronger self-directed learning capabilities, enhancing their readiness for workforce integration and lifelong professional development. These insights highlight the necessity of innovative curriculum strategies to bridge the gap between academic learning and practical skill acquisition, offering valuable guidance for educators seeking to improve vocational education outcomes.
Volume: 14
Issue: 4
Page: 3273-3282
Publish at: 2025-08-01

Deep learning algorithms for breast cancer detection from ultrasound scans

10.11591/ijict.v14i2.pp427-437
Lawysen Lawysen , Gede Putra Kusuma
Breast cancer is a highly dangerous disease and the leading cause of cancer related deaths among women. Early detection of breast cancer is considered quite challenging but can offer significant benefits, as various treatment interventions can be initiated earlier. The focus of this research is to develop a model to detect breast cancer based on ultrasound results using deep learning algorithms. In the initial stages, several preprocessing processes, including image transformation and image augmentation were performed. Two types of models were developed: utilizing mask files and without using mask files. Two types of models were developed using four deep learning algorithms: residual network (ResNet)-50, VGG16, vision transformer (ViT), and data-efficient image transformer (DeiT). Various algorithms, such as optimization algorithms, loss functions, and hyperparameter tuning algorithms, were employed during the model training process. Accuracy used as the performance metric to measure the model’s effectiveness. The model developed with ResNet-50 became the best model, achieving an accuracy of 94% for the model using mask files. In comparison, the model developed with ResNet-50 and DeiT became the best model for the model without mask files, with an accuracy of 80%. Therefore, it can be concluded that using mask files is crucial for producing the best-performing model.
Volume: 14
Issue: 2
Page: 427-437
Publish at: 2025-08-01

Interests of Gen Zs in rural communities: insights to strengthen the delivery of the Philippine PATH-Fit program

10.11591/ijere.v14i4.33515
Jr., Ruben L. Tagare , Jomar B. Esto , Desiree Ann C. Tenebroso , Jeahr E. Inabangan , William R. Pregunta , Erika P. Acera , Jan Lincoln C. Rivas , Claribel P. Avila , Pink Floyd M. Boyles
This study investigated the local interests of Generation Z (Gen Z) students in rural communities to strengthen the delivery of the Philippine physical activity towards health and fitness (PATH-Fit) program. Using a qualitative-ethnographic approach, insights were gathered from 20 carefully selected Gen Z students through open-ended questions validated by experts. The findings revealed seven key areas of interest: i) social media, videos, and the internet; ii) something profitable; iii) e-games; iv) sports and physical activities; v) going out and exploring; vi) church, reflection, and music; and vii) rest and sleep. This study concludes that the local interests of Gen Z students in rural communities paint a comprehensive picture of a generation adeptly balancing the digital and physical realms of their lives. From the appeal of social media, online ventures, and e-games to the grounding effects of sports, nature exploration, and spiritual practices, these students demonstrate a flexible approach to well-being and personal growth. Their focus on profitable online activities reflects a pragmatic response to economic challenges, while their commitment to physical activities and outdoor exploration underscores the importance of maintaining a healthy lifestyle. Their emphasis on church, reflection, music, rest, and sleep also highlights a holistic understanding of mental and emotional health. Together, these interests reveal a resourceful, adaptive generation that is deeply aware of the need for balance in an increasingly complex world.
Volume: 14
Issue: 4
Page: 3260-3272
Publish at: 2025-08-01

Understanding e-book acceptance from a resource-based view perspective: an analysis among students at UiTM Melaka

10.11591/ijere.v14i4.32111
Zulkefli Muhamad Hanapiyah , Ahmad Fadhly Arham , Muhammad Syukri Abdullah , Muhammad Fairuz Jamil , Nor Sabrena Norizan , Wei-Loon Koe
The COVID-19 pandemic led to a shift in the Malaysian education system from traditional face-to-face teaching to online and open distance learning (ODL). This transition has impacted students, lecturers, and universities. E-books are one technology that supports online learning at the university level. This study aims to investigate the factors influencing e-book acceptance among students. Using quantitative research, a questionnaire was administered to 171 students at Universiti Teknologi MARA (UiTM), Melaka Campus, who are enrolled in strategic management course. The findings reveal a significant impact of course content, instructors, and university support on e-book acceptance. However, there was no significant effect observed for access ability, computer competency and infrastructure. These insights are crucial for universities to plan and implement e-books effectively for their students. As the study is specific to UiTM Melaka Campus, it is recommended that future research encompasses both public and private universities for a more comprehensive understanding.
Volume: 14
Issue: 4
Page: 2742-2748
Publish at: 2025-08-01

Advanced deep attention neural inference network for enhanced arrhythmia detection and accurate classification

10.11591/ijeecs.v39.i2.pp1164-1175
H. Sumitha , M. Devanathan
Arrhythmias are irregular heartbeats that can lead to severe health risks, including sudden cardiac death, necessitating accurate and timely detection for effective treatment. Traditional diagnostic methods such as stress tests, resting electrocardiograms (ECGs), and 24-hour Holter monitors are limited by their monitoring capacity and often result in delayed diagnoses, compromising patient safety. To address these challenges, this paper introduces the deep attention neural inference network (DANIN) methodology. DANIN integrates one-dimensional ECG signals with two-dimensional spectral images using multi-modal feature fusion, capturing comprehensive cardiac information in both temporal and frequency domains. The methodology employs advanced deep attention network-based models for superior feature extraction, recognizing intricate patterns and long-range dependencies within the data. Additionally, the inclusion of an inference model system enhances interpretability and usability, making the model highly suitable. Further, DANIN is evaluated considering the MIT-BIH dataset, and extensive comparative analysis with state-of-the-art techniques demonstrates that DANIN significantly improves accuracy, precision, recall, and F1-score, highlighting its potential to revolutionize arrhythmia detection and improve patient outcomes.
Volume: 39
Issue: 2
Page: 1164-1175
Publish at: 2025-08-01

Handling missing values and clustering industrial liquid waste using K-medoids

10.11591/ijeecs.v39.i2.pp1411-1420
Ratih Hafsarah Maharrani , Prih Diantono Abda'u , Ganjar Ndaru Ikhtiagung , Nur Wahyu Rahadi , Zaenurrohman Zaenurrohman
The textile industry is a significant contributor to environmental pollution due to its wastewater, which contains hazardous substances such as dyes, heavy metals, and chemicals that can severely harm aquatic ecosystems. Effective management of this wastewater is crucial to mitigate its environmental impact. This study focuses on classifying industrial liquid waste data using the K-medoids clustering method, chosen for its robustness to noise and outliers compared to K-means. To address challenges in wastewater data processing, such as missing values and varying data scales, two approaches are compared: replacing missing values with zero and K-nearest neighbors (KNN) imputation, alongside Z-score normalization for data uniformity. The clustering quality is evaluated using the Davies-Bouldin index (DBI) for cluster variations of k=2, 3, 4, and 5. The results show that the best clustering quality is achieved at k=2, with the smallest DBI values obtained using KNN imputation (0.139) and zero replacement (0.149). The superior performance of KNN imputation highlights its effectiveness in handling missing data. These findings provide valuable insights into the characteristics of textile industry wastewater pollution, offering a robust framework for effective wastewater management. The study concludes with practical recommendations for policymakers and industry stakeholders to adopt advanced data-driven approaches for sustainable wastewater treatment strategies.
Volume: 39
Issue: 2
Page: 1411-1420
Publish at: 2025-08-01

Integrating artificial bee colony and cauchy algorithms for distribution network reconfiguration with soft open points

10.12928/telkomnika.v23i4.26129
Nguyen; Electric Power University Tung Linh , Nguyen; Electric Power University Quynh Anh
Reconfiguring the distribution network by selecting open switch states is an effective approach to reduce power losses in the system. However, with the rise of distributed energy resources such as photovoltaic and wind turbines and dynamic loads such as electric vehicles, which introduce uncertainties, it has become necessary to integrate standard operating procedures (SOPs) to better control power flows. This study proposes an algorithm that combines the artificial bee colony (ABC) and Cauchy opposition-based learning (OBL) algorithms to solve the optimization problem of determining both the location and capacity of SOPs, alongside reconfiguring the distribution network. The primary objective is to minimize power losses while improving power quality and system reliability. The proposed methodology was validated on the IEEE 33-node and 69-node distribution networks under seven varied operational scenarios, evaluating outcomes both with and without the integration of SOPs. The findings demonstrate that installing SOPs optimally reduces power losses, enhances system reliability, and maintains voltage levels within acceptable limits. The integration of the two algorithms also accelerates the convergence process, increasing computational speed and avoiding local optimization issues. When compared with other methods, the proposed algorithm delivers similar performance but with faster computation times and fewer iterations, making it more efficient and reliable.
Volume: 23
Issue: 4
Page: 1069-1083
Publish at: 2025-08-01

Developing a robust data integrity verification framework for cloud storage utilizing Boneh-Lynn-Shacham signatures

10.12928/telkomnika.v23i4.26709
Raed; Northern Technical University Abdulkareem Hasan , Mustafa; Imam Aadham University College M. Akawee , Enas; Northern Technical University Faek Aziz , Omar A.; Collage/Fallujah University Hammood , Tole; Universitas Ahmad Dahlan Sutikno
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.
Volume: 23
Issue: 4
Page: 1097-1107
Publish at: 2025-08-01

A compact five-band patch antenna covering WLAN, WiMAX, X, and Ku-bands

10.12928/telkomnika.v23i4.27017
Suthasinee; Rajamangala University of Technology Isan Khonkaen Campus Lamultree , Wutthipong; Rajamangala University of Technology Isan Khonkaen Campus Thanamalapong , Kanawat; Rajamangala University of Technology Isan Khonkaen Campus Nuangwongsa , Charinsak; Rajamangala University of Technology Isan Khonkaen Campus Saetiaw
This paper introduces a compact, low-profile, five-band antenna for wireless communication systems operating across 2.4/5 GHz WLAN, 3.5 GHz WiMax, and 7.5 GHz X- and Ku-band frequencies. The proposed antenna utilizes a novel configuration with a dual-overlapping rectangular patch coupled to a wide circular slot and an inverted L-shaped strip. Fabricated on a single-layer FR4 substrate (εr=4.3, thickness=1.6 mm), the antenna employs a 50-ohm coplanar waveguide feed, resulting in a compact footprint of 40×40×1.6 mm³. Experimental measurements and simulations demonstrate a bidirectional radiation pattern covering five distinct frequency bands: 2.4-2.485 GHz, 3.4-3.6 GHz, 5.15-5.825 GHz, 7.25-8.4 GHz, and 13.4-17.7 GHz. The antenna exhibits a return loss better than 10 dB across all bands and provides average gains of 1.78 dBi, 3.04 dBi, 3.4 dBi, 4.27 dBi, and 4.46 dBi, respectively. These results confirm the successful development of a five-band antenna with excellent performance characteristics, making it a promising candidate for 2.4/5 GHz WLAN, WiMax, and X- and Ku-band satellite communications, with automotive vehicles being one example.
Volume: 23
Issue: 4
Page: 906-917
Publish at: 2025-08-01

Increasing learning innovation through developing teachers’ basic abilities in professional development supervision

10.11591/ijere.v14i4.28913
Rifma Rifma , Ranti Meizatri , Rudinal Rusdinal , Jasrial Jasrial
Learning innovation is always related to teacher abilities, emphasizing the design and implementation of innovative teaching and learning. This study aimed to assess the effects of professional development-supervised teacher basic abilities on learning innovation. A total of 409 teachers were engaged as participants. In this case, supervision experience was obtained with a teacher basic ability development approach (commitment and abstraction), as data were analyzed using the partial least square structural equation model (PLS-SEM). The results showed that teacher basic abilities significantly affected the success of professional development supervision and learning innovation. This indicated that the influential levels of the basic abilities on learning innovation and professional development supervision emphasized the t-statistics/p-values of 37.535≥1.96/0.000 and 39.492≥1.96/0.000, respectively. The effects of professional development supervision on learning innovation were also characterized by the t-statistics and p-value of 39.492≥1.96 and 0.000, respectively. Meanwhile, the teacher basic abilities significantly impacted the combined activities of professional development supervision and learning innovation through the t-statistic and p-value of 8.283≥1.96 and 0.000, respectively. These results recommended that principals and supervisors should consider teachers basic abilities as a target in the supervision of professional development, to realize sustainable learning innovations.
Volume: 14
Issue: 4
Page: 3089-3102
Publish at: 2025-08-01
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