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27,404 Article Results

Studentsโ€™ character based on gender, grade, and school: religious, nationalism, integrity, independent and cooperative

10.11591/ijere.v14i3.29347
An-Nisa Apriani , Riki Perdana , Harun Harun , Indah Perdana Sari , Wury Wuryandani , Ahmad Salim , Andi Wahyudi , Riwayani Riwayani
This study aims to describe studentsโ€™ character value and reveal the relationship of character values in elementary school children based on gender, grade and type of the school. The character values analyzed include religion, nationalism, integrity, independence, and cooperative values. This research was a quantitative method with a cross-sectional design by explaining and analyzing the results using Jeffreyโ€™s amazing statistics program (JASP) software and studentsโ€™ character values was categorized and described according to the aspect, gender, grade, and type of the school. Character of elementary school children (CESC) questionnaire was used as an instrument in this study. CESC have very good internal consistency (0.80 to 0.87) and have suitability construct model. The respondent of this study was 862 students obtained through the stratified random sampling randomly technique in elementary school at Yogyakarta Province. The result of this study confirmed that the studentsโ€™ character value is a high level. The lowest aspect is integrity (2.40), while the highest aspect is religious (3.16). There is a relationship between the character values: religion, nationalism, integrity, independent, and cooperative values. It indicates that policymakers or teachers should improve studentsโ€™ character value by training or applying a learning model that focuses explicitly on studentsโ€™ character.
Volume: 14
Issue: 3
Page: 1916-1929
Publish at: 2025-06-01

Factors affecting engineering studentsโ€™ self-perceived employability in Morocco

10.11591/ijere.v14i3.31797
Zineb Sabri , Ahmed Remaida , Benyoussef Abdellaoui , Abdessalam Ait Madi , Aniss Qostal , Fatima Ezzahra Chadli , Youssef Fakhri , Aniss Moumen
In a dynamic socio-economic world, perceiving a career opportunity and job prospects has become complex. The number of unemployed individuals is rising despite the increasing number of students pursuing higher education. This study is suggested to enhance studentsโ€™ professional insertion, guide their career development initiatives, and help them acquire the skills demanded by prospective employers, thereby increasing their likelihood of employment. For this goal, this study investigates the determinants impacting self-perceived employability (SPE) among engineering students. Following a quantitative approach to explain how personal and contextual factors impact perceived employability, more than 350 Moroccan engineering students responded to a questionnaire for data collection, which had an internal consistency of 0.90. Data analysis employing advanced statistical techniques using structural equations modeling (SEM) to conduct descriptive, regression, and mediation analysis. The findings highlight that academic performance, university contribution, and personal circumstances significantly influence perceived employability, while generic skills have a minor effect. Furthermore, personal determinants are identified as stronger than contextual ones. The results provide several recommendations to stakeholders such as university administrations, teaching staff, employers, the Ministry of Education, and graduates. Additionally, they offer an insightful exploration of the intricate interactions among factors that enhance employability.
Volume: 14
Issue: 3
Page: 2132-2143
Publish at: 2025-06-01

The computer, information and communication technology, and communication skills of Thai Rajabhat University students

10.11591/ijere.v14i3.32461
Sunan Siphai , Jirattikorn Siphai , Jittirat Saengloetuthai , Jaruwan Sakulku
The lack of comprehensive data on computer, information and communication technology (ICT), and communication skills among Thai Rajabhat University students poses a challenge in developing effective educational strategies that enhance student employability and future readiness. To address this gap, this study aimed to assess these skills and analyze the skill profiles of students from Rajabhat Universities across Thailand. A total of 1,165 students were selected through multi-stage sampling, and their skills were measured using a researcher-developed 5-point Likert scale questionnaire. The results showed high levels of self-reported skills, with communication skills being the highest (mean=3.84, SD=0.669), followed by ICT (mean=3.81, SD=0.676) and computer skills (mean=3.65, SD=0.628). Latent profile analysis (LPA) identified four potential models with 2, 3, 4, and 5 groups, with the four-group model offering the best fit (likelihood=-1887.336, Akaike information criterion (AIC)=3810.673, Bayesian information criterion (BIC)=3901.762, Akaikeโ€™s Bayesian information criterion (ABIC)=3844.587, entropy=0.940). These findings provided critical insights for curriculum development and tailored interventions, supporting universities in meeting diverse student needs and improving educational outcomes.
Volume: 14
Issue: 3
Page: 1752-1760
Publish at: 2025-06-01

Bridging technology and humanity: humanizing online pedagogy in digital environments

10.11591/ijere.v14i3.31937
Nor Asiah Razak , Che Zalina Zulkifli , Yusri Abdullah , Ahmad Zulfadhli Khairuddin , Aervina Misron , Piriya Somasundram , Azizova Gulnora Shakirdjanovna
Comprehensive analyses on incorporating the intersection of online education, humanizing teaching approaches, and digital tools remain scarce. To the best of the authors' knowledge, limited comprehensive studies integrate online pedagogy and digital tools to humanize teaching methods, enabling students to become engaged and personalized learners, while fostering empathy among educators. A systematic literature review (SLR) was conducted, utilizing databases from the Scopus, Web of Science (WoS), and Google Scholar. The study employed content and comparative analysis and advocated a grounded theory approach to inductively analyses and navigate the articlesโ€™ data for addressing three research questions. Based on a set of criteria for inclusion and exclusion, 34 research articles written in English between 2010 and 2024 were reviewed. Results indicated the community of inquiry (CoI) framework has been prominent over the past two decades and is considered suitable for integration with any digital tools when investigating pedagogical strategies at all education levels, aiming to make online learning student-centered or human-centered with the principle of โ€˜no child left behind'. The review offers significant implications for humanizing online learning to the educational technology community, particularly for policymakers and practitioners, to strategies, reflect on, and, if necessary, improve their practices for future sustainable education and efficient pedagogical performance.ย 
Volume: 14
Issue: 3
Page: 2207-2223
Publish at: 2025-06-01

Pioneering educational frontiers: South Korea-ASEAN synergy in big data integration and future innovations

10.11591/ijere.v14i3.31828
Catherine Joy T. Escuadra , Ella Joy Avellanoza Ponce
This study examines the evolving trends in publication collaboration and research topics related to big data and education in South Korea and the Association of Southeast Asian Nations (ASEAN) region, analyzed through the lens of international relations (IR). Using scientometric methods, the study analyzed 2,427 publications from Web of Science (WoS) throughย R Studio and VOSViewer, highlighting a marked increase in publication volume, citation, and collaboration in recent years. The research focuses on key areas such as the integration of big data in teaching and performance assessment, the intersection of big data with artificial intelligence (AI), and the varying implementation frameworks across different countries. The findings reveal that while significant progress has been made, there is a need for more structured collaborative efforts. To enhance future research output and collaboration, the study recommends establishing international research networks, organizing joint projects, facilitating exchange programs, and investing in necessary infrastructure. Additionally, it suggests developing policy frameworks and securing funding to support these initiatives. Engaging industry partners and expanding collaborative networks are crucial for advancing the field and optimizing the application of big data in education.
Volume: 14
Issue: 3
Page: 2007-2017
Publish at: 2025-06-01

Challenges and opportunities in strategic educational planning: a systematic literature review

10.11591/ijere.v14i3.32750
Semail Endo , Abdul Halim Busari , Dayang Kartini Abang Ibrahim
Strategic educational planning is essential for adapting to the evolving landscape of education, driven by socio-economic, technological and exceptional global health crisis. This systematic literature review explores the complex challenges and opportunities in strategic educational planning, synthesizing insights from diverse studies to provide a comprehensive understanding. The problem statement addresses the necessity for effective strategic planning to ensure educational resilience, quality and inclusivity amidst changing external conditions. To achieve this, we conducted an extensive search of scholarly articles from reputable databases such as Scopus and Web of Science, focusing on studies published between 2020 and 2024. The flow of study based on preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework. The database found (n=33) final primary data was analyzed. The finding was divided into three themes which is: i) educational strategies and innovations; ii) organizational and strategic management in education; and iii) impact and adaptation to external challenges in education. The review indicate that strategic educational planning must prioritize flexibility, stakeholder engagement and continuous improvement to navigate future challenges effectively. This review underscores the fundamental role of strategic planning in transforming educational systems to be more adaptive, inclusive and forward-thinking, ultimately enhancing their capacity to meet the diverse needs of learners in an ever-changing global context.
Volume: 14
Issue: 3
Page: 1621-1632
Publish at: 2025-06-01

Deep learning-based secured resilient architecture for IoT-driven critical infrastructure

10.11591/ijeecs.v38.i3.pp1819-1829
Srinivas A. Vaddadi , Rohith Vallabhaneni , Sanjaikanth E. Vadakkethil Somanathan Pillai , Santosh Reddy Addula , Bhuvanesh Ananthan
While enabling remote management and efficiency improvements, the infrastructure of the smart city becomes able to advance due to the consequences of the internet of things (IoT). The development of IoT in the fields of agriculture, robotics, transportation, computerization, and manufacturing. Based on the serious infrastructure environments, smart revolutions and digital transformation play an important role. According to various perspectives on issues of privacy and security, the challenge is heterogeneous data handling from various devices of IoT. The critical IoT infrastructure with its regular operations is jeopardized by the sensor communication among both IoT devices depending upon the attacker targets. This research suggested a novel deep belief network (DBN) and a secured data dissemination structure based on blockchain to address the issues of privacy and security infrastructures. The non-local means filter performs pre-processing and the feature selection is achieved using the improved crystal structure (ICS) algorithm. The DBN model for the classification of attack and non-attack data. For the non-attacked data, the security is offered via a blockchain network incorporated with the interplanetary file system.
Volume: 38
Issue: 3
Page: 1819-1829
Publish at: 2025-06-01

Trust evaluation in online social networks for secured user interactions

10.11591/ijeecs.v38.i3.pp2070-2078
Anitha Yarava , C. Shoba Bindu
Online social network is a good platform, where users can share their opinions, ideas, products, and reviews with known (friends and relatives) and unknown users. The growing fame and its easy accesses of new users sometimes lead to security and privacy issues. Many methods are reported so far to address these issues but usage of high complex cryptographic algorithms creating new set of performance related challenges to the mobile users. In this paper, light weight soft security (trust) method is proposed. The proposed method โ€œTrust evaluation in online social networks for secured user interactions-TEOSNโ€ uses user social activities in estimation of his trustworthiness. Each user is observed in terms of followed factor-๐‘“๐‘‘ (his interactions with others) and follower factor-๐‘“๐‘Ÿ (others interaction with him). The factors ๐‘“๐‘‘ and ๐‘“๐‘Ÿ are estimated using fuzzy logic and user trust-๐œ is estimated using beta distribution. The performance of TEOSN is verified theoretically and practically. In experimental results, TEOSN is verified against different number of users; especially it outperformed existing methods in trust computation of target users at 2 to 4-hop distances.
Volume: 38
Issue: 3
Page: 2070-2078
Publish at: 2025-06-01

Blue light therapy device for wound healing

10.11591/ijeecs.v38.i3.pp1527-1539
Minahil Kamal , Aleena Kamal , Azka Abid , Sarah Ahmed , Syed Muddusir Hussain , Jawwad Sami Ur Rahman , Sathish Kumar Selvaperumal
Cuts, diabetic ulcers, and pressure sores are examples of chronic skin wounds that pose a serious healthcare danger because of their delayed healing rates. This problem emphasizes the necessity of creating noninvasive, economical, and successful wound treatment plans. Conventional treatments, such as skin grafting, negative pressure wound therapy, and hyperbaric oxygen therapy, have demonstrated effectiveness; nevertheless, they are frequently costly, intrusive, and have possible side effects. On the other hand, blue light treatment has become a viable substitute due to its antimicrobial characteristics and capacity to encourage cellular restoration. However, there is a crucial gap in the development of a portable, noninvasive, and cost-effective photobiomodulation device for wound treatment and monitoring, despite its demonstrated potential in wound healing. This work aims to address this gap by creating a novel blue light therapy tool specifically suited for wound healing. The gadget allows for controlled blue light exposure and real-time temperature monitoring to minimize overheating. It has a portable arm housing with integrated blue light strips, a temperature sensor, and an integrated fan. An STM 32 microcontroller powers the systemโ€™s pulse width modulation (PWM) technology, which modifies light intensity and therapy duration in response to conditions unique to each wound. This novel strategy seeks to improve the effectiveness of wound healing, lower the likelihood of adverse effects, and offer patients and healthcare providers a workable alternative that is noninvasive, inexpensive, and easy to use.
Volume: 38
Issue: 3
Page: 1527-1539
Publish at: 2025-06-01

Unraveling the predictors of research utilization among Thai educators: evidence from PLS-SEM analysis

10.11591/ijere.v14i3.31468
Phuchit Laowang , Suntonrapot Damrongpanit
This groundbreaking study unveils critical factors driving research utilization (RU) among Thai educators, offering vital insights for educational policymakers and administrators. Employing an advanced partial least squares structural equation modeling (PLS-SEM) approach, we examined data from 688 teachers under the office of the basic education commission. Our findings reveal a complex interplay of factors influencing RU, with organizational support (SUPP) emerging as the most potent driver (beta=0.570), followed by knowledge and research skills (KNOWS) (beta=0.539), organizational leadership (LEAD) (beta=0.472), and attributes of research (ATTR) (beta=0.391). Interestingly, ATTR showed the highest direct effect (DE) (beta=0.391), while LEAD had the strongest indirect impact (beta=0.429). Surprisingly, organizational climate (ORGA) showed no significant effect, challenging conventional wisdom. The study explains 52.5% of the variance in RU, providing a robust foundation for evidence-based educational reforms. Delve into our analysis to discover how these relationships between knowledge, leadership, and organizational dynamics shape educational RU in Thailand, and explore our recommendations for enhancing research integration in educational practices.
Volume: 14
Issue: 3
Page: 1684-1694
Publish at: 2025-06-01

A simple machine learning technique for sensor network wireless denial-of-service detection

10.11591/ijeecs.v38.i3.pp1690-1697
Shaik Abdul Hameed , Ravindra Kumar Indurthi , Gopya Sri Arumalla , Venkatesh Bachu , Lakshmi S. N. Malluvalasa , Venkateswara Rao Peteti
Wireless sensor networks (WSNs) are integral to numerous applications but are vulnerable to denial-of-service (DoS) attacks, which can severely compromise their functionality. This research proposes a lightweight machine learning approach to detect DoS attacks in WSNs. Specifically, we investigate the efficacy of decision tree (DT) algorithms with the Gini feature selection method, alongside random forest (RF), extreme gradient boosting (XGBoost), and k-nearest neighbor (KNN) classifiers. Data collected from normal and DoS attack scenarios are preprocessed and used to train these models. Experimental results showcase the effectiveness of the proposed approach, with the DT algorithm exhibiting high accuracy exceeding 90%, surpassing other classifiers in computational efficiency and interpretability. This study contributes to enhancing the security and reliability of WSNs, offering insights into potential future optimizations and algorithmic explorations for robust DoS attack detection.
Volume: 38
Issue: 3
Page: 1690-1697
Publish at: 2025-06-01

Holographic-based design, building, and testing of an RRP spherical robot for olive fruits harvesting

10.11591/ijeecs.v38.i3.pp1602-1612
Osama M. Al-Habahbeh , Ayeh Arabiat , Riad Taha Al-Kasasbeh , Salam Ayoub
A revolute-revolute-prismatic (RRP) spherical robot has been designed, simulated, built, and tested. The robot is intended to perform olive fruit harvesting tasks. The design simulation is done using hologram tools. The design factors considered include reach, dexterity, accuracy, and productivity. Based on the results of the holographic simulation, a prototype was built and tested on real olive fruits. The end effector is equipped with a rake tool so that the robot can harvest multiple fruits in each stroke. The robot is controlled by Raspberry Pi while a stereovision camera enables 3-D vision. Once the camera detects the fruits, an inverse kinematics algorithm is initiated to find the location of the fruits. The fruit coordinates are commanded to the manipulator to perform the harvesting. The field tests showed that the manipulator is successful in performing the harvesting operations. To increase the harvesting efficiency, it is recommended to build a larger prototype.
Volume: 38
Issue: 3
Page: 1602-1612
Publish at: 2025-06-01

Ba3GdNa(PO4)3F:Eu2+ phosphor with blue-red emission colors on white-LED properties

10.11591/ijeecs.v38.i3.pp1564-1571
Nguyen Van Dung , Nguyen Doan Quoc Anh
The blue/red-emission phosphor Ba3GdNa(PO4)3F:Eu2+ (BGN(PO)F-Eu) is used in this work for diodes emit white illumination (wLED). The phosphor is prepared using the solid-phase reaction. The suitable concentrations of Eu2+ ion dopant is about 0.7% and 0.9%. The BGN(PO)F-Eu phosphor can provide wLED light with the spectral wavelength in the region of blue (480 nm) and orange-red colors (595-620 nm). With the resulted emissions the phosphor can be appropriate for plant growing because they compatible with absorption spectra of plantsโ€™ carotenoids and chlorophylls for stimulating the photosynthesis. The phosphor influences on the wLED lighting properties depending on the doping dosages. It is possible to enhance the luminous intensity of the wLED with higher BGN(PO)F-Eu phosphor amount. Meanwhile, the color properties does not get significant improvements. Thus, the BGN(PO)F-Eu phosphor could be used with other luminescent materials to stimulate the hue rendering performance.
Volume: 38
Issue: 3
Page: 1564-1571
Publish at: 2025-06-01

Weierstrass scale space representation and composite dilated U-net based convolution for early glaucoma diagnosis

10.11591/ijeecs.v38.i3.pp1661-1672
Abdul Basith Zahir Hussain , Sulthan Ibrahim Mohamed Sulaiman
Glaucoma is one of the common causes of blindness in the current world. Glaucoma is a blinding optic neuropathy characterized by the degeneration of retinal ganglion cells (RGCs). Accurate diagnosis and monitoring of glaucoma are challenging task through eye examinations and additional tests. To achieve accurate diagnosis of glaucoma with higher sensitivity and specificity, novel method called Weierstrass scale space representation and composite dilated U-net based convolution (WSSR-CDC) is introduced. At first, the Weierstrass transform scale space representation is employed to enhance image structures at various scales with higher accuracy of region of interest (ROI) detection using Eulerโ€™s identity. Next, CDC model is utilized with several layers. In input layer, preprocessed input images are taken as input. Fragment derivative are formulated for every preprocessed input. Log cosh dice loss function and optic cup to disc ratio are computed for segmented glaucoma detected results. With this, the accurate diagnosis of glaucoma is made with minimal error. The WSSR-CDC method was evaluated using the glaucoma fundus imaging dataset with several factors. The results show that the WSSR-CDC method outperforms conventional techniques, improving accuracy by 24% and sensitivity by 18%. It demonstrates promising results in fast, accurate, diagnosis of glaucoma.
Volume: 38
Issue: 3
Page: 1661-1672
Publish at: 2025-06-01

Novel prostate cancer detection and classification model using support vector machine

10.11591/ijeecs.v38.i3.pp1681-1689
Kandukuri Sujata , Bokka Sridhar , Avala Mallikarjuna Prasad
Prostate cancer (PCa) is one of the most common and deadliest cancers that kill men worldwide with high mortality and prevalence especially in developed countries. PCa is regarded as one of the most prevalent cancers and is one of the main causes of deaths worldwide. Early detection of PCa diseases helps in making decisions about the progressions that should have occurred in high-risk patients decrease their risks. The recent developments in technology and methods have given rise to computer aided diagnosis (CAD). Early cancer detection can greatly increase the chance of survival through the administration of the proper treatment. Due to the emerging trends and available datasets in state-of-art machine learning (ML) and deep learning (DL) techniques, there has been significant growth in recent disease prediction and classification publications. This paper presents a unique support vector machine-based model for PCa detection and classification. This analysis aims to classify the PCa using ML algorithm and to determine the risk factors. Support vector machines (SVM) is used to identify and classify the PCa. Accuracy, sensitivity, specificity, precision, and F1-score are the measurements used to evaluate the performance of the presented method. This model will achieve accuracy, sensitivity, specificity, precision, and F1-score than earlier models.
Volume: 38
Issue: 3
Page: 1681-1689
Publish at: 2025-06-01
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