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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 874 Documents
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Integrating Social Intelligence Into Character-Based Education: A Contextual Learning Model in Modern Boarding Schools Sabaruddin; Rusli Yusuf; Misri A. Muchsin; Masrizal
Emerging Science Journal Vol. 9 (2025): Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-SIED1-015

Abstract

Objectives: This study designs and evaluates a social intelligence-based learning model for social studies in modern Islamic boarding schools (pesantren) in Indonesia, addressing the lack of social-emotional integration in faith-based curricula. Methods/Analysis: A mixed-methods approach involved 150 participants from five pesantren, including students, teachers, and school leaders. Qualitative data were gathered via interviews, observations, documentation, and FGDs, while quantitative data were collected using a validated 25-item Social Skills Questionnaire. Descriptive statistics, paired-sample t-tests, and Cohen’s d assessed effectiveness, with methodological and theoretical triangulation ensuring qualitative validity. Findings: The model—integrating social values, interactive strategies, contextual materials, authentic assessment, and teacher facilitation produced significant gains in social intelligence. Problem-solving and tolerance improved most (+1.7 points each), and student participation rose from 42% to 88%. Both students and teachers reported high satisfaction with the collaborative, contextually relevant approach. The questionnaire demonstrated high reliability (Cronbach’s α = 0.87). Novelty/Improvement: This study introduces a culturally grounded, faith-based pedagogical framework embedding social intelligence into character-based education. By aligning Islamic values and Acehnese wisdom with 21st-century social competencies it provides a replicable model for enhancing social-emotional learning in similar educational contexts.
Modeling and Performance Optimization for Complex Workflow in IoT Lu, Ting; Li, Huiling; Zeng, Qingtian; Duan, Hua; Liu, Cong
Emerging Science Journal Vol. 9 No. 5 (2025): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-05-02

Abstract

This study addresses the growing challenge of time scheduling in Internet of Things (IoT) workflows, where efficiency in time utilization and resource profitability is increasingly constrained by uncertainty. Real-world workflows are characterized by non-deterministic activity execution and resource preparation times, yet existing research often neglects these fundamental dynamics when modeling IoT-based processes. To bridge this gap, we propose a comprehensive modeling and performance optimization framework that explicitly incorporates uncertainty. Methodologically, the framework introduces two distinct types of places to represent activities and resources, with resource properties capturing reusability and preparation processes abstracted as specialized activities. For workflow activities, timing functions are defined to model minimum and maximum execution times, enabling the computation of earliest and latest start times and the identification of critical activities driving overall workflow duration. To mitigate resource conflicts during execution, three alternative resolution strategies are developed and systematically evaluated. Results demonstrate that the proposed approach effectively identifies optimal scheduling strategies under uncertainty, enhancing both temporal efficiency and resource utilization. A workflow case study illustrates the applicability of the framework, offering methodological and practical insights for designing resilient IoT workflow scheduling systems in complex, real-world environments.
E-Service Quality and Loyalty Driving E-Satisfaction and E-WOM in Higher Education Nguyen, Vi T. T.; Truong, Tue G.; Nguyen, Thanh D.
Emerging Science Journal Vol. 9 (2025): Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-SIED1-019

Abstract

This study examines the influence of core e-service quality dimensions, information quality, website performance, and website confidentiality, on perceived emotional value, e-satisfaction, student loyalty, and electronic word-of-mouth (e-WOM) within the digital delivery of higher education services in Vietnam. Drawing upon the Stimulus–Organism–Response (SOR) framework, the Expectation–Confirmation Theory (ECT), and the Value-Based Adoption Model (VAM), this research investigates behavioral outcomes through psychological mediators. Data were collected from 311 university students with prior experience in using their universities’ electronic service platforms, including learning and academic management systems. Measurement scales were adapted from established studies, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS–SEM). The results reveal that e-service quality positively influences perceived emotional value, which subsequently drives e-satisfaction, student loyalty, and e-WOM. Furthermore, student loyalty reinforces e-WOM, underscoring the critical role of digital engagement in higher education. This study contributes to existing theory by integrating service quality dimensions, emotional responses, and behavioral intentions into a unified model. It also offers practical insights for enhancing student engagement, optimizing digital learning environments, and strengthening institutional reputation in today’s increasingly competitive digital education landscape.
DC Motor Angular Speed Controller Using an Embedded Microcontroller-Based PID Controller Ma'arif, Alfian; Nugraha, Ikhwan; Maghfiroh, Hari; Furizal; Suwarno, Iswanto
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-03

Abstract

This research presents the implementation of a Proportional Integral Derivative (PID) controller to control the angular speed of a Direct Current (DC) motor using an embedded system (microcontroller). The system’s hardware consists of an Arduino microcontroller, a DC motor with an encoder sensor, a driver motor, and a power supply. Proportional control regulates the response proportionally to the calculated error, while integral control manages the cumulative error over time, and derivative control responds to the rate of change of the error, preventing overshoot. With a proper combination, PID control achieves stability, speeds up response, and reduces overshoot, improving overall system performance. Based on experimental data, the DC motor angular speed control system using PID control achieves the best results, in which the parameter values are Kp=1; Ki=0.3; and Kd=0.6. The augmented system responded with 0.0890 seconds of the rise time, 11.772 seconds of settling time, and 0.12 seconds of the peak time, with an overshoot of less than 10% (7%).
Cognitive and Affective Analysis in Water Education and Literacy Through Educational Robotics in Elementary School De la Hoz Serrano, Alejandro; Melo Niño, Lina Viviana; Piedade, Joào; Cañada Cañada, Florentina; Cubero Juánez, Javier
Emerging Science Journal Vol. 9 (2025): Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-SIED1-020

Abstract

The aim of this study was to examine the impact of Educational Robotics on the cognitive and affective development of primary school students in the context of water education and literacy, with a specific focus on learning the water cycle and healthy hydration habits. A quasi-experimental design with a mixed-methods approach was adopted, involving a sample of 158 students (83 girls and 75 boys). The educational intervention consisted of 12 sessions incorporating interactive activities supported by robotics, and data were collected through pre- and post-intervention questionnaires. The findings revealed significant improvements in scientific knowledge, with students reaching an Excellent level in understanding the water cycle and a Sufficient level in hydration-related content. From an affective perspective, positive emotions such as Joy and Enjoyment (81.82%) were predominant, especially in relation to methodological and content aspects, whereas negative emotions were primarily linked to challenges in teamwork and oral communication. The novelty of this study lies in highlighting the value of Educational Robotics not merely as a motivational tool but as a meaningful technological support for learning scientific content. These results emphasize the importance of further research into Educational Robotics potential and the need to address affective barriers to optimize learning outcomes.
Enhanced Optimization Strategy to Maximize Achievable Rate of Millimeter-Wave Full-Duplex UAV on Multiple User Harinitha, Dwi; Zakia, Irma; Iskandar
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-07

Abstract

This study proposes an enhanced optimization strategy to maximize the achievable data rate of millimeter-wave (mmWave) full-duplex (FD) unmanned aerial vehicles (UAVs) in multi-user scenarios. The objective is to address signal degradation from high-frequency path loss and self-interference while ensuring efficient resource allocation across multiple user equipment (UEs). A joint optimization framework is introduced, integrating UAV positioning, beamforming vector design at both the gateway and UAV, and power allocation. Initially, the Alternating Interference Suppression (AIS) algorithm is adapted for multiple UEs, but due to emerging non-convexity, the problem is reformulated using a first-order approximation approach. The solution is decomposed into two iterative sub-problems—optimizing UAV location and then solving for beamforming and power distribution. MATLAB-based simulations validate the proposed approach, revealing a threefold increase in achievable data rate and a 40.85% improvement in power efficiency compared to non-optimized systems. The novelty of this work lies in its scalable multi-user adaptation and its integrated, power-aware optimization algorithm, outperforming conventional FD and half-duplex strategies. This contribution significantly advances the design of efficient, high-throughput UAV communication systems for next-generation wireless networks, especially in environments with frequent line-of-sight obstructions.
Small Dual Polarized UWB Antenna and Its Array Analysis for 5G/6G Applications Dastkhosh, Amir Reza; Mehbodniya, Abolfazl; Webber, Julian; Naseh, Mehdi; Dadras Jedi, M.; Lin, Fujiang
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-04

Abstract

In this work, a novel low-profile tunable ultra-wideband (UWB) K/Ka-band (14–40 GHz) dual circularly polarized magneto-electric antenna element has been designed, analyzed, and validated through circuit modeling, simulations, fabrication, and experimental testing for application in 5G/6G phased-array antennas. The antenna has compact dimensions of 0.5λ₀× 0.5λ₀ × 0.06λ₀/0.09λ₀, which can be further reduced to 0.25λ₀× 0.25λ₀ × 0.05λ₀ when metal–insulator–metal (MIM) and/or gap capacitors are employed. The proposed antenna exhibits a high gain of 9 dB, a wide scanning angle of ±75°, and an efficiency exceeding 85% across the entire operating frequency band. In addition, it demonstrates high isolation between ports and between co-polarized and cross-polarized radiation patterns, reaching 25 dB. The resonant frequency of the antenna is tunable, with a variation of up to 97% over the K/Ka-band frequency range. This tuning capability is achieved using MIM capacitors connected to the vias of the circular patch and/or gap capacitors, which collectively function as split-ring resonators (SRRs). Fabrication and experimental testing of the antenna confirm good agreement with the simulated results. The antenna is easily fabricated using glass substrates and standard epoxy/glass processes with only two layers, making it highly suitable for antenna-in-package applications based on glass technology. Since the antenna element is specifically designed for phased-array applications, array configurations were also investigated. Analysis of 512-element arrays shows that the Sunflower layout provides enhanced gain and overall performance while utilizing more than 50% fewer antenna elements compared to a conventional rectangular array.
Multi-Objective Optimization of Injection Molding Using Taguchi, Fuzzy Methods, and GA Moayyedian, Mehdi; Chalak Qazani, Mohammad Reza; Hedayati-Dezfooli, M.; Mussin, Askhat; Bissekenova, Zhanel
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-028

Abstract

The objective of this research is to optimize the injection molding process of an automotive window regulator bracket by improving the moldability index while minimizing key defects. To achieve this, a multi-objective framework is developed that combines the Taguchi method with Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy-TOPSIS. Five critical processing parameters—melt temperature, mold temperature, filling time, holding pressure time, and cooling time—were investigated, with polypropylene as the base material. A Taguchi L25 orthogonal array was employed to reduce the number of experimental trials from 3,125 to just 25, thereby saving resources while maintaining reliability. The evaluation considered warpage, residual stress, and shear stress, which are the most influential defects affecting part performance. Finite Element Analysis (FEA) was incorporated to validate the accuracy of the results, while a hybrid ANFIS-GA predictive model was applied to forecast the moldability index, demonstrating an improvement of about 1% over conventional optimization methods. The optimized settings resulted in minimized warpage (1.8122 mm), residual stress (43.03 MPa), and shear stress (0.08 MPa). The novelty of this work lies in integrating Taguchi with FAHP and Fuzzy-TOPSIS for a single-objective transformation, offering a systematic and efficient approach for multi-objective optimization in injection molding applications.
YOLOv10-MsA: Attention-Augmented Real-Time Insulator Defect Detection from UAV Imagery Yang, Junbiao; Mat Isa, Nor Ashidi
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-02

Abstract

The reliable operation of transmission systems depends on early detection of defects within high-voltage insulators because it helps stop power outages. Scalable inspection remains a challenge since UAV-based imagery and deep learning generate recent promising solutions. The goal of this study is to build an accurate and time-efficient insulator defect detection system through the YOLOv10 architecture integration of Manhattan Self-Attention (MsA), which strengthens spatial feature detection and increases robustness during evaluations in complex aerial inspection scenarios. The designers implemented the MsA modules into the backbone and neck sections of YOLOv10 to develop YOLOv10-MsA as their novel detection model. The model relied on 5,000 annotated insulator images acquired by unmanned aerial vehicles throughout various defect classes during training and evaluation. Standard object detection metrics consisting of mAP@0.5, mAP@0.5:0.95, precision, recall, F1-score, and inference speed evaluated the performance of the model. The YOLOv10-MsA system reached an mAP@0.5 performance of 93.1% and an F1-score of 91.9% at an inference speed of 79 FPS, which surpasses YOLOv8, YOLOv9, and baseline YOLOv10. The model demonstrated its best performance at detecting various small and hard-to-detect defects such as chipping and contamination. The application of MsA in detection systems resulted in better accuracy while preserving real-time operation, according to related model assessment. The proposed YOLOv10-MsA serves as a powerful deployable system for UAV-based insulator inspection because it achieves both high accuracy and fast operation. The method establishes conditions for real-time smart infrastructure observation with attention-augmented frameworks for object detection.
LH-Moments Parameter Estimation of Weibull Distribution Guayjarernpanishk, Pannarat; Chiangpradit, Monchaya
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-014

Abstract

Natural disasters such as sudden floods, storms, severe snowfall, and droughts are major problems in the world. Generally the distributions of extreme values are heavy-tailed distributions, and an important heavy-tailed distribution is the Weibull distribution, especially for non-linear behaviors. Therefore, accurately estimation of the occurrence of disasters is required to deal with such situations in a timely and efficient manner. Several methods can be used to estimate the parameters, for example, moments estimate, maximum likelihood estimate, linear of moment, and high-order L-moments. The objectives of this article are to estimate the parameters of the four-parameter Weibull distribution with weak non-linear effects (W4DN) based on the LH-moments method, and to propose a new parameter estimation formula. The proposed formula is classified into two cases based on the coefficient of the second-order term (δ): Case 1, where the coefficient is positive (δ > 0) and Case 2, where the coefficient is negative (δ < 0). In both cases, the corresponding estimation formulas are derived βr and λrp for p=1, 2, ... and r=1, 2, ..., respectively. The parameter estimations (γ ̂,α ̂,δ ̂,ϕ ̂ and κ ̂) are then optimized using the augmented Lagrangian adaptive barrier minimization algorithm. These formulas provide a practical approach for parameter estimation that is essential for forecasting extreme events in various disciplines, including hydrology, meteorology, insurance, finance, and engineering.

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