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27,404 Article Results

The application of fuzzy Delphi method for the development of STEM teaching model

10.11591/ijere.v14i3.29780
Zhaofeng Zeng , Xin Li , Siew Wei Tho
In order to improve the ability of physics student teachers (PSTs) to teach using the science, technology, engineering, and mathematics (STEM) teaching model, this study applied the fuzzy Delphi method (FDM) to determine the constituent items that need to be included in the process of constructing the STEM teaching model according to the characteristics of PSTs. A questionnaire through literature review and expert advice was prepared, which contained 17 items in three constructs, including eight items for cultivating students’ abilities, four for teaching strategy design, and five for the expected outcomes. Then, the questionnaire was distributed to 16 experts to collect opinions and suggestions, which were analyzed and ranked using the FDM. The findings showed that all 17 items passed the expert consensus, all the specialist consensus values above 75%, the threshold values (d) ≤0.2, and the fuzzy scores (A) ≥α-cut value=0.5. Within the framework of the study and based on expert consensus, it is necessary for the newly developed STEM teaching model for PSTs to incorporate all 17 items across three constructs. This would optimally enhance the PSTs’ ability to employ the STEM teaching model in their teaching instruction.
Volume: 14
Issue: 3
Page: 2061-2069
Publish at: 2025-06-01

The effectiveness of edutainment in teaching cell cycle and transport mechanisms

10.11591/ijere.v14i3.30810
Emman A. Litera , Minie L. Bulay
Traditional lecture-based teaching methods prevalent in Philippine schools often lead to passive learning. By contrast, this study investigates the active engagement and enhanced conceptual comprehension facilitated by edutainment through Classcraft v.4.2.6, focusing on the least learned competencies of cell cycle and transport mechanisms. Expert evaluation of edutainment content affirmed its potential as a valuable educational tool. Students exposed to the edutainment method showed significantly improved learning outcomes compared to those taught via traditional lecture method, as validated by statistical analyses. However, challenges such as technological barriers and distractions were acknowledged. To optimize edutainment’s benefits, strategic design considerations and support mechanisms are recommended, including purposeful design, progressive complexity, and educator training. This study significantly updates knowledge in educational practices by highlighting edutainment’s efficacy. By challenging lecture-based teaching, it advocates for more engaging instructional approaches in Philippine secondary education, promising enhanced learning experiences and outcomes.
Volume: 14
Issue: 3
Page: 2400-2408
Publish at: 2025-06-01

Leveraging active learning practices for effectiveness of higher education: performance based investigation

10.11591/ijere.v14i3.30325
Vignesh Saravanan Kirubakara , Swarna Sudha Muppudathi , Jothi Thilaga Paul Ayyadurai , Sakthi Priya Gomathi Nayagam
Engineering graduates in India struggle with employability due to outdated curricula and ineffective teaching methods, which limit their ability to apply knowledge and think critically. A performance-based study investigated the impact of active learning (AL) techniques in technical education using methods like concept mapping, role-playing, virtual labs, and collaborative coding in computer science and engineering courses. The findings showed a 35% to 40% improvement in academic results compared to traditional methods, along with significant boosts in student engagement, comprehension, and critical thinking. Student feedback and performance evaluations strongly favored AL. Cluster analysis revealed fewer slow learners, highlighting its effectiveness in meeting diverse needs. The study concludes that integrating AL can better prepare students for the job market and enrich their educational experience.
Volume: 14
Issue: 3
Page: 2327-2336
Publish at: 2025-06-01

Research capability of Filipino teacher educators: insights from a criterion-referenced test

10.11591/ijere.v14i3.32849
Jay-cen T. Amanonce , Conchita M. Temporal , Rudolf T. Vecaldo , Jhoanna B. Calubaquib , Antonio I. Tamayao , Maribel F. Malana , Ria A. Tamayo , Marie Claudette M. Calanoga
The research capability of Filipino teacher educators has been found to be lacking, which limits their ability to contribute effectively to academic research. This study aims to assess their foundational knowledge in research, as understanding their capability is essential for improvement. A quantitative approach was employed, evaluating 100 teacher educators from a state university in Northern Philippines using the research capability test (RCT), a validated criterion-referenced tool. Results showed that teacher educators generally possess average research capability, with significant differences based on educational attainment, field of specialization, and research teaching experience. Those with doctoral degrees, specializations in natural sciences and mathematics, and experience teaching research demonstrate higher capability. These findings suggest that, while basic research knowledge exists, there is a critical need for focused professional development programs to address specific gaps. Strengthening research capability not only improves the teacher educators’ performance but also enhances the overall quality of research outputs in the Philippine education system, ensuring long-term academic growth and global competitiveness.
Volume: 14
Issue: 3
Page: 1706-1716
Publish at: 2025-06-01

Enhancing preservice teachers’ collaborative problem solving through STEM project-based learning

10.11591/ijere.v14i3.27725
Rita Fitriani , Hadi Suwono , Ibrohim Ibrohim , Betty Lukiati
This study aimed to determine the effect of science, technology, engineering, and mathematics project-based learning (STEM-PjBL) on the collaborative problem solving (CPS) of preservice teachers (PSTs). The pretest-posttest non-equivalent control group design was employed. A total of 72 PSTs enrolled in plant physiology course participated in this study. Self-assessment and project were used to evaluate PSTs’ CPS skills. Self-assessment scores were analyzed by analysis of covariance (ANCOVA), while project scores were analyzed by the Mann-Whitney U test. The results of self-assessment indicated that STEM-PjBL enhances CPS skills, particularly in social regulation, task regulation, and knowledge building. The results of the team’s problem-solving skills in completing the project did not differ between the two groups. But the result of integrated STEM skills showed that the STEM-PjBL group was better at integrating STEM disciplines into their project. This study highlights the importance of interdisciplinary projects in a PjBL environment that can be adopted by teacher preparation programs for enhancing PSTs’ CPS skills as well as gaining knowledge of STEM integration.
Volume: 14
Issue: 3
Page: 2278-2289
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

Study of a model of a satellite structure that meets the necessary criteria for stability and rotation in space

10.11591/ijaas.v14.i2.pp502-512
Mahmoud Fadhel Idan , Osamah Mahmood Hussein
The study aimed to create a model of a satellite structure that meets the necessary criteria for stability and rotation in space. The satellite being analyzed has an octagonal shape, with a diameter of 110 cm and a height of 85 cm. A dynamic modeling approach was used to analyze the structural properties, and the finite element method (FEM) was employed for computational analysis. This method allowed for a comprehensive evaluation of stress, displacement, and vibration distribution throughout the structure, providing insight into the behavior of the communications satellite in space. The test model frame consists of plates and bars arranged in an octagonal shape. The analysis utilized the von Mises stress (σvM) criterion to assess the yield strength or brittleness of the chosen material, 7,057 aluminum alloy. The study revealed that the structure demonstrates stability in six different modes but also exhibits deformation due to modifications in the basic arrangement. Additionally, transient fluctuations in the spacecraft's position over a 24-hour cycle result in changes in torque. The structure remains stable within a specified frequency range starting at 150 Hz when subjected to vibration stimuli, and no external instability was detected within this range.
Volume: 14
Issue: 2
Page: 502-512
Publish at: 2025-06-01

Impact of natural-white and red-blue light-emitting diode lighting on hydroponic basil growth and energy efficiency

10.11591/ijaas.v14.i2.pp406-415
Chaiyant Boonmee , Warunee Srisongkram , Wipada Wongsuriya , Patcharanan Sritanauthaikorn , Paiboon Kiatsookkanatorn , Napat Watjanatepin
Advanced phosphor-converted white light-emitting diodes (pc-WLEDs) have been developed to mimic the natural sunlight spectrum, potentially enhancing plant growth compared to traditional red-blue (R-B) LEDs. This study aimed to compare the effects of natural-white pc-WLED (nsW-pcLED) and conventional R-B LED (R:B 3.24) on the growth, yield, and energy efficiency of hydroponically grown sweet basil. It was cultivated in a deep-water culture system under identical conditions with a photosynthetic photon flux density (PPFD) of 200±10 µmol·m⁻²·s⁻¹ and a 16/8 light/dark photoperiod over 28 days. Key growth parameters, including plant height, stem diameter, leaf number, and plant fresh weight (PFW), were measured, while energy consumption was recorded to assess efficiency. Results indicated that nsW-pcLED significantly enhanced growth, with plants achieving an average height of 44.30±1.51 cm, stem diameter of 6.68±0.21 mm, and a PFW of 34.20±6.12 g, compared to 35.88±4.05 cm, 4.66±0.88 mm, and 23.02±5.26 g under R-B LED (p <0.05), respectively. The nsW-pcLED treatment produced an average net growth of 1,221 g·m⁻² versus 536.43 g·m⁻² for R-B LED and delivered 33.05 g·m⁻²·kW·h⁻¹ compared to 11.17 g·m⁻²·kW·h⁻¹, while consuming 23% less energy. These findings highlight nsW-pcLED’s superior performance for indoor hydroponic cultivation. Future studies should explore its application in large-scale systems and across diverse crop species.
Volume: 14
Issue: 2
Page: 406-415
Publish at: 2025-06-01

Optimization of cashew apple extract as a tomato sauce substitute in chicken steak marinades

10.11591/ijaas.v14.i2.pp590-597
Siti Susanti , Fatma Puji Lestari , Agus Setiadi , Budi Hartoyo , Ahmad Ni'matullah Al-Baarri
This study aims to optimize the use of cashew apple extract (CAE) as a substitute for tomato sauce in marinades and evaluate its effects on the chemical and sensory qualities of chicken steak. Four different marinade formulations containing varying concentrations of CAE (0, 5, 10, and 15%) were applied to chicken steak samples. Chemical analyses measured protein, fat content, and polycyclic aromatic hydrocarbon (PAH) levels, while sensory evaluations were conducted to assess tenderness, juiciness, aroma, and overall preference using a semi-trained panel. The results demonstrated that increasing CAE concentrations significantly elevated protein content (p<0.05) and reduced fat levels. PAH levels were below detectable limits in all samples, suggesting the marinade’s potential in reducing PAH formation. Sensory analysis revealed that the 5% CAE marinade was the most preferred, particularly for tenderness and juiciness. These findings suggest that CAE is a viable alternative to tomato sauce in marinades, offering both nutritional benefits and consumer acceptability.
Volume: 14
Issue: 2
Page: 590-597
Publish at: 2025-06-01

Combining XGBoost and hybrid filtering algorithm in e-commerce recommendation system

10.11591/ijaas.v14.i2.pp618-626
Vincentius Loanka Sinaga , Antoni Wibowo
This study proposes a hybrid filtering algorithm (HFA) that combines extreme gradient boosting (XGBoost), content-based filtering (CBF), and collaborative filtering (CF) to improve recommendation accuracy in electronic commerce (e-commerce). XGBoost first leverages demographic data (e.g., age, gender, and location) to address cold start conditions, producing an initial product prediction; CBF refines this prediction by measuring product similarities through term frequency-inverse document frequency (TF-IDF) and cosine similarity, while CF (implemented via singular value decomposition) further incorporates user interaction patterns to enhance recommendations. Experimental results across multiple datasets demonstrate that HFA consistently outperforms standalone XGBoost in key metrics, including precision, F1-score, and hit ratio (HR). HFA’s precision often exceeds 90%, indicating fewer irrelevant recommendations. Although recall levels remain modest, HFA exhibits stronger adaptability under cold start scenarios due to its reliance on demographic features and user-item interactions. These findings highlight the efficacy of combining advanced machine learning with hybrid filtering techniques, offering a more robust and context-aware solution for e-commerce recommendation systems.
Volume: 14
Issue: 2
Page: 618-626
Publish at: 2025-06-01

Enhancing artificial neural network performance for energy efficiency in laboratories through principal component analysis

10.11591/ijaas.v14.i2.pp310-321
Desmira Desmira , Norazhar Abu Bakar , Mustofa Abi Hamid , Muhammad Hakiki , Affero Ismail , Radinal Fadli
This study investigates energy efficiency challenges during laboratory activities. Inefficient energy use in the practicum phase remains a critical issue, prompting the exploration of innovative forecasting models. This research employs artificial neural network (ANN) models integrated with principal component analysis (PCA) to predict energy consumption and optimize usage. The findings reveal that PCA components, including eigenvalues, eigenvectors, and matrix covariance values, significantly influence the ANN model's performance in forecasting energy production. The ANN training achieved a high correlation coefficient (R=1) with a mean squared error (MSE) of 0.045931 after 200,000 epochs, demonstrating the model's robustness. While testing results showed a moderate correlation (R=0.46169), the models demonstrated potential for refinement and scalability. This integration of ANN and PCA models provides a reliable framework for accurately forecasting energy usage, offering an effective strategy to enhance energy efficiency in laboratory settings. By optimizing energy consumption, this approach has the potential to reduce operational costs and environmental impact. The strong performance metrics highlight the practical utility of these models in educational contexts, contributing to sustainable energy management and better resource allocation. Furthermore, the reduction in energy-related environmental impacts underscores the broader applicability of these models for fostering sustainable development in similar contexts.
Volume: 14
Issue: 2
Page: 310-321
Publish at: 2025-06-01

Comparative study on fine-tuning deep learning models for fruit and vegetable classification

10.11591/ijaas.v14.i2.pp384-393
Abd Rasid Mamat , Mohamad Afendee Mohamed , Mohd Fadzil Abd Kadir , Norkhairani Abdul Rawi , Azim Zaliha Abd Aziz , Wan Suryani Wan Awang
Fruit and vegetable recognition and classification can be a challenging task due to their diverse nature and have become a focal point in the agricultural sector. In addition to that, the classification of fruits and vegetables increases the cost of labor and time. In recent years, deep learning applications have surged to the forefront, offering promising solutions. Particularly, the classification of fruits using image features has garnered significant attention from researchers, reflecting the growing importance of this area in the agricultural domain. In this work, the focus was on fine-tuning hyperparameters and the evaluation of a state-of-the-art deep convolutional neural network (CNN) for the classification of fruits and vegetables. Among the hyperparameters studied are the number of batch size, number of epochs, type of optimizer, rectified unit, and dropout. The dataset used is the fruit_vegetable dataset which consists of 36 classes and each class contains 1,000 images. The results show that the proposed model based on the batch size=64 and the number of epochs=25, produces the most optimal model with an accuracy value (training) of 99.02%, while the validation is 95.73% and the loss is 6.06% (minimum).
Volume: 14
Issue: 2
Page: 384-393
Publish at: 2025-06-01

Security analysis of Indonesia e-commerce platform against the risk of phishing attacks

10.11591/ijaas.v14.i2.pp533-541
Gede Arna Jude Saskara , Made Ody Gita Permana , I Made Gede Sunarya
This research analyses the security of e-commerce platforms in Indonesia against the risk of phishing attacks using the social-engineer toolkit (SET) application. Of the 31 platforms tested, it was found that 22 platforms have a low-security level because they can be easily replicated to carry out phishing attacks. In contrast, 9 platforms showed a high level of security, as they implemented the step-wise authentication and embedded login methods, which proved effective in protecting the platform from phishing attacks. The effectiveness rate of the SET application in conducting tests was recorded at 70.9%; the percentage is included in the high category. This research also identified that most low-security platforms still use the single-page login method or a special URL for login, making them very vulnerable to phishing attacks. The action research method was used as the research framework, involving five stages: diagnosis, planning, action, evaluation, and learning. The results of this study provide important guidance for platform owners to improve security mechanisms, how to build a login page to avoid the risk of misuse by cybercrime actors to conduct phishing attacks, and for users as a reference to choose a more secure e-commerce platform.
Volume: 14
Issue: 2
Page: 533-541
Publish at: 2025-06-01

Usability evaluation of ToAksara as Balinese script learning mobile application

10.11591/ijaas.v14.i2.pp490-501
Gede Indrawan , Sariyasa Sariyasa , Luh Joni Erawati Dewi , Made Santo Gitakarma , I Made Agus Oka Gunawan , Putu Ade Pranata
ToAksara application transliterates Latin text into Balinese script and has been used in high school teaching and learning activities in Buleleng Regency, Bali, Indonesia. This application was expected to provide comfort and satisfaction for students while learning the Balinese language and script. To measure the comfort and satisfaction level, a usability evaluation was carried out that focused on the application's end user. This research used a combination of concurrent think-aloud (CTA) and user experience questionnaire (UEQ) to evaluate ToAksara. In CTA, data collection involved nine respondents given a task scenario and expressing their problems or input. In UEQ, data collection involved 385 respondents who chose the value closest to their impression of 26 statements. Based on the analysis results, CTA produced several recommendations for improving the application regarding navigation, functionality, and errors. Based on the analysis, the user satisfaction results showed that all aspects were included in the excellent category. The aspects of attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty each produced a value of 2.144, 2.220, 2.385, 2.345, 2.139, and 2.101. The excellent category shows that ToAksara was included in the range of the top 10% of products compared to the UEQ benchmark.
Volume: 14
Issue: 2
Page: 490-501
Publish at: 2025-06-01

Energy efficient direct transesterification of Nannochloropsis sp. using hydrodynamic cavitation

10.11591/ijaas.v14.i2.pp394-405
Jiran Nirmalasari , Martomo Setyawan , Siti Jamilatun , Joko Pitoyo , Dhias Cahya Hakika
The increasingly limited supply of fossil fuels requires renewable fuel as an alternative source. Nannochloropsis sp. is a microalgae species containing a lipid content of between 12 and 53%, which can be converted to biofuel as an alternative source of fossil fuels through a transesterification process. Up to this date, the literature has reported no studies on biodiesel production from Nannochloropsis sp. via direct transesterification with catalyst using hydrodynamic cavitation. The direct transesterification process introduced 7.5 g of microalgae, 40 ml of methanol, 90 ml of hexane, and 0.0225 g of sodium hydroxide into the sample chamber. These mixtures were passed within the cavitation using a pressure driver and transformed into fatty acid methyl ester (FAME). The catalytic hydrodynamic cavitation method produces a higher extract yield than the stirring one. Regarding the FAME composition, the catalytic hydrodynamic cavitation method is dominated by saturated fatty acid (palmitic), while the stirring catalytic method is dominated by monounsaturated fatty acid (oleic). The hydrodynamic cavitation method provides a lower average degree of unsaturation and shorter chain length than the stirring catalytic method.
Volume: 14
Issue: 2
Page: 394-405
Publish at: 2025-06-01
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