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25,002 Article Results

Character education content in science textbook for senior high school students

10.11591/ijere.v14i1.26389
Kintan Limiansi , Suranto Suranto , Paidi Paidi , Darmiyati Zuchdi
Student textbooks need to contain character education following curriculum objectives. This study aimed to describe the character content in high school science textbooks 10th-grade, analyze the distribution of character content on each topic, and identify similarities in each textbook. The research objectives were answered by inferential content analysis. The books analyzed were two textbooks (one published by the government and one published by a private company). The results showed that both textbooks contained dimensions of the Pancasila student profile presented explicitly and implicitly. The analysis showed that the character content in book 1 was 262 and in book 2 was 463. Book 1 is dominated by critical reasoning (39%) and book 2 is dominated by independence (34%). The distribution of characters on each topic in the two books is different, but both books contain all dimensions of the character profile of Pancasila students. The results of this study are considered for teachers to use various books and learning resources in learning. In addition, the results of this study also provide initial information for future researchers to develop a mechanism for measuring the profile of Pancasila students as a feature of the Independent Curriculum.
Volume: 14
Issue: 1
Page: 28-36
Publish at: 2025-02-01

Enhancing sentiment analysis through deep layer integration with long short-term memory networks

10.11591/ijece.v15i1.pp949-957
Parul Dubey , Pushkar Dubey , Hitesh Gehani
This involves studying one of the most important parts of natural language processing (NLP): sentiment, or whether a thing that makes a sentence is neutral, positive, or negative. This paper presents an enhanced long short-term memory (LSTM) network for the sentiment analysis task using an additional deep layer to capture sublevel patterns from the word input. So, the process that we followed in our approach is that we cleaned the data, preprocessed it, built the model, trained the model, and finally tested it. The novelty here lies in the additional layer in the architecture of LSTM model, which improves the model performance. We added a deep layer with the intention of improving accuracy and generalizing the model. The results of the experiment are analyzed using recall, F1-score, and accuracy, which in turn show that the deep-layered LSTM model gives us a better prediction. The LSTM model outperformed the baseline in terms of accuracy, recall, and f1-score. The deep layer's forecast accuracy increased dramatically once it was trained to capture intricate sequences. However, the improved model overfitted, necessitating additional regularization and hyperparameter adjustment. In this paper, we have discussed the advantages and disadvantages of using deep layers in LSTM networks and their application to developing models for deep learning with better-performing sentiment analysis.
Volume: 15
Issue: 1
Page: 949-957
Publish at: 2025-02-01

Communication competence model: how to train ability to say what you really mean

10.11591/ijere.v14i1.29806
Nataliia Glushanytsia , Tetyana Tarnavska , Nadiia Chernukha , Zoriana Krupnyk , Dmytro Kostenko
Business is becoming increasingly multinational. Non-native language communication is a background activity for many jobs and a challenge for those whose first language is not English. The problem is that a non-native language activity distracts attention, increases the risk of misunderstanding, and reduces the effectiveness of professional communication. The article aims to present a Foreign Language Communicative Competence model that is a way to solve the problem and enables fluent, errorless communication that supports professional activity. The main question of the research is what learning conditions, methods and strategies, approaches, and technologies provide the development of foreign language communication competence. We used questionnaires, interviews, psychological diagnostic techniques, observations, and a pedagogical experiment in the research. The pedagogical experiments occurred at the National Aviation University in the 2021 to 2022 academic year. Two groups of second-year students majoring in “Aviation Maintenance” were involved. The experiment outcomes show the enhanced level of students’ foreign language communication competence, motivation, and engagement in learning. The developed model contributes to the ability to concentrate on the job and make quick decisions under the influence of psychological factors like time pressure, stress, or noise while speaking a foreign language.
Volume: 14
Issue: 1
Page: 708-719
Publish at: 2025-02-01

Comparison of machine learning algorithms to identify and prevent low back injury

10.11591/ijece.v15i1.pp894-907
Christian Ovalle Paulino , Jorge Huamani Correa
With the advancement of technology, remote work and virtual classes have become increasingly common, leading to prolonged periods in front of computers and, consequently, to discomfort and even lower back pain. This study compares machine learning algorithms to identify and prevent low back pain, a common health problem. A predictive model for early diagnosis and prevention of these injuries was developed using datasets from open data repositories. Six machine learning models were used to train the data. Results showed that logistic regression was the most effective model, with performance curves of 70%, 90%, and 99%. Performance metrics indicated 86% accuracy, 85% recall, and 86% F1-score. Accuracy of 70%, recall of 71%, and F1-score of 63% reflect the robust ability of the model to address the problem. In addition, an intuitive interface was implemented using Gradio Software to improve data visualization.
Volume: 15
Issue: 1
Page: 894-907
Publish at: 2025-02-01

Acceptance of 21st century elements education among teachers in Malaysia

10.11591/ijere.v14i1.24863
Nasir Nayan , Hanifah Mahat , Mohmadisa Hashim , Yazid Saleh , Edi Kurniawan , Nurul Khotimah
Malaysia’s education development plan 2013-2025 promotes 21st-century learning. Instruction, learning, and school assistance are the key focus. This study selected Rompin State instructors to assess their 21st-century education ability, perspective, and application. The questionnaire was the main data-gathering tool in this quantitative investigation. Standard random sampling chose 152 school teachers. This study used Pearson correlation and t-test for descriptive and inferential analysis. The results showed reasonable knowledge, attitude, and practices (mean=2.95, standard deviation=0.22, 2.94, 0.23, 2.90, 0.29). The t-test showed significant differences in knowledge (t=-2.11, df=157, p 0.05) and attitude (t=-2.26, p 0.05) but not in practice (t=-1.81, p>0.05). Using Pearson correlation analysis, knowledge, and behaviors were moderately positively correlated (r=0.677, p<0.01), whereas attitudes and practices were strongly positively correlated (r=0.837, p<0.1). Teachers have modest knowledge, attitudes, and practices. Teachers must frequently take short courses to improve their 21st-century education. Mandatory authorities and scholars will help instructors professionally grasp 21st-century education. This study found that teachers with 21st-century education literacy can improve their knowledge, attitude, and practice and regularly apply it to their teaching.
Volume: 14
Issue: 1
Page: 250-259
Publish at: 2025-02-01

Using digital tools in STEM education and the impact on student creativity in the field of tribology

10.11591/ijere.v14i1.30220
Мazhyn Skakov , Sherzod Ramankulov , Мakpal Nurizinova , Bakitzhan Kurbanbekov , Yelmurad Dossymov
From a preliminary analysis of the scientific literature, it can be seen that knowledge of science, technology, engineering and mathematics (STEM) has a positive impact on the development of necessary skills in students’ professional activities. However, there are very few studies on the effectiveness of using STEM elements in developing the creativity of future physics teachers in specialized fields. The aim of this study was to develop digital resources as a basis for STEM knowledge and to assess their impact on the development of students’ creativity. Based on special principles of education, constructive method in teaching, modeling methods, digital educational resources were developed and an evaluation experiment was conducted. The experiment involved 86 students (40 in the control group and 46 in the experimental group), and compared the results of traditional learning and STEM learning by using digital resources. The results of the questionnaire assessment showed that STEM education can be very effective in developing students’ creativity. The pedagogical experiment was implemented during the teaching of the author’s course entitled “The physical foundations of tribology.” The results of the study contribute to finding solutions to scientific problems in the field of teaching tribology.
Volume: 14
Issue: 1
Page: 589-597
Publish at: 2025-02-01

Seasonal auto-regressive integrated moving average with bidirectional long short-term memory for coconut yield prediction

10.11591/ijece.v15i1.pp783-791
Niranjan Shadaksharappa Jayanna , Raviprakash Madenur Lingaraju
Crop yield prediction helps farmers make informed decisions regarding the optimal timing for crop cultivation, taking into account environmental factors to enhance predictive accuracy and maximize yields. The existing methods require a massive amount of data, which is complex to acquire. To overcome this issue, this paper proposed a seasonal auto-regressive integrated moving average-bidirectional long short-term memory (SARIMA-BiLSTM) for coconut yield prediction. The collected dataset is preprocessed through a label encoder and min-max normalization is employed to change non-numeric features into numerical features and enhance model performance. The preprocessed features are selected through an adaptive strategy-based whale optimization algorithm (AS-WOA) to avoid local optima issues. Then, the selected features are given to the SARIMA-BiLSTM to predict the coconut yields. The proposed SARIMA-BiLSTM is adaptable to handling a widespread of various seasonal patterns and captures spatial features. The SARIMA-BiLSTM performance is estimated through the coefficient of determination (R2), mean absolute error (MAE), mean squared error (MSE), and root mean square error (RMSE). SARIMA-BiLSTM attains 0.84 of R2, 0.056 of MAE, 0.081 of MSE, and 0.907 of RMSE which is better when compared to existing techniques like multilayer stacked ensemble, convolutional neural network and deep neural network (CNN-DNN) and autoregressive moving average (ARIMA).
Volume: 15
Issue: 1
Page: 783-791
Publish at: 2025-02-01

Impact of self-esteem and overall life satisfaction on perceived social competence in university students

10.11591/ijere.v14i1.30056
Muhammad Kamran , Marwa Saab , Urooj Niaz , Sarfraz Aslam , Amjad Islam Amjad
Positive psychology is transformative in developing individuals’ self-esteem, life satisfaction, subjective happiness, and social competence. The objectives of the present study were to investigate the impact of self-esteem and overall life satisfaction on perceived social competence in university students while measuring subjective happiness as a mediator and gender differences across variables. A sample of 1,168 participants was selected using purposive and random sampling techniques across universities in Pakistan. The study design was correlational with a quantitative method. Four scales, the Rosenberg self-esteem scale (RSE), satisfaction with life scale (SWLS), subjective happiness scale (SHS), and perceived social competence scale (PSCS), were administered to measure the variables. Pearson correlation and mediation models were used to test the hypotheses. The analysis indicated that subjective happiness mediated the relationship between self-esteem, perceived social competence, life satisfaction, and perceived social competence. Moreover, the results showed that males scored higher than females in terms of levels of self-esteem. No significant gender difference existed in life satisfaction, subjective happiness, and perceived social competence. These findings may significantly enrich the literature on positive psychology in Pakistani university students and can assist universities in their mental health programs and sustain students’ healthier well-being.
Volume: 14
Issue: 1
Page: 310-318
Publish at: 2025-02-01

Evaluating machine learning models for predictive analytics of liver disease detection using healthcare big data

10.11591/ijece.v15i1.pp1162-1174
Osama Mohareb Khaled , Ahmed Zakareia Elsherif , Ahmed Salama , Mostafa Herajy , Elsayed Elsedimy
Liver diseases rank among the most prevalent health issues globally, causing significant morbidity and mortality. Early detection of liver diseases allows for timely intervention, which can prevent the progression of such diseases to more severe stages such as cirrhosis or liver cancer. To this end, many machine learning models have been previously developed to early predict liver diseases among potential patients. However, each model has its accuracy and performance limitations. In this paper, we present a comprehensive comparison of three different machine learning models that can be employed to enhance the prediction and management of liver diseases. We utilize a big data set of 32,000 records to evaluate the performance of each model. First, we implement a preprocessing technique to rectify missing or corrupt data in liver disease datasets, ensuring data integrity. Afterwards, we compare the performance of three machine models: k-nearest neighbors (KNN), gaussian naive Bayes (Gaussian NB) and random forest (RF). We concluded that the RF algorithm demonstrates superior performance in our evaluation, excelling in both predictive accuracy and the ability to classify patients accurately regarding the presence of liver disease. Our results show that RF outperforms other models based on several performance metrics including accuracy: 97.3%, precision: 97%, recall: 96%, and f1-score: 95%.
Volume: 15
Issue: 1
Page: 1162-1174
Publish at: 2025-02-01

The role of authoritative parenting and self-regulation in controlling adolescent aggressiveness

10.11591/ijere.v14i1.26650
Muhamad Hasan Abdillah , Zurqoni Zurqoni , Wildan Saugi , Ibnu Sutoko
Seeing the many cases of adolescent violence that occurred in Yogyakarta, Indonesia, this study was interested in examining the suitability of authoritative parenting and self-regulation abilities to the level of adolescent aggressiveness. The subjects of this study were 154 class XII students of State Senior High School 1 Sleman. The sample selection was obtained using a stratified random sampling technique. The aim is to obtain student representation from each class. Researchers use the scale as the main tool in obtaining research data on aggressiveness, authoritative parenting and self-regulation. The data was then analyzed using multiple linear regression with the SPSS V26 program. The results of the analysis showed that, simultaneously, authoritative parenting and self-regulation were very significant in suppressing the emergence of aggressiveness in adolescents (F=51.76 and Sig.=.000). Then, both authoritative parenting (Beta=-.37 with Sig.=.000) and self-regulation (Beta=-.35 with Sig.=.000) both were able to have a significant effect on adolescent aggressiveness partially. The conclusion is that adolescents need authoritative parenting at this phase; this is necessary to avoid the emergence or development of aggressiveness in adolescents. Besides that, adolescents must also be equipped with self-regulation skills because most activities are carried out without parental supervision.
Volume: 14
Issue: 1
Page: 452-462
Publish at: 2025-02-01

Theoretical framework used in parental involvement research: a scoping review

10.11591/ijere.v14i1.29392
Novia Solichah , Nur Ainy Fardana , Samian Samian
Theoretical perspectives are important in framing a research model of parental involvement. Despite numerous studies examining parental involvement, their findings continue to exhibit inconsistency when viewed through a theoretical lens. A literature review conducted in 2017 examined the theoretical frameworks employed in parental involvement studies conducted between 2007 to 2011. The primary objective of this study is to analyze and offer novel insights into the theoretical perspectives that underpin parental involvement research, adhering to PRISMA guidelines. We conducted an extensive study of literature published between 2012 to 2023 that met the following inclusion criteria: research papers, reports on parental involvement, and reports on theoretical framework. Our study encompassed a systematic search of electronic databases, including Scopus, EBSCO Sciences, Emerald, and Science Direct from July to September 2023 to identify relevant articles. A total of 366 articles were obtained, and 44 articles met the criteria. Four theories frequently utilized in parental involvement research emerged from this study, namely Bronfenbrenner’s Bioecological Theory; Bourdieu, Coleman, and Lareau’s social capital; Social Identity Theory; and Ajzen’s Theory of Planned Behavior. The findings of this research serve as a foundational resource for future research on parental involvement across diverse contextual settings.
Volume: 14
Issue: 1
Page: 758-767
Publish at: 2025-02-01

Arabic fake news detection using hybrid contextual features

10.11591/ijece.v15i1.pp836-845
Hussain Mohammed Turki , Essam Al Daoud , Ghassan Samara , Raed Alazaidah , Mais Haj Qasem , Mohammad Aljaidi , Suhaila Abuowaida , Nawaf Alshdaifat
Technology has advanced and social media users have grown dramatically in the last decade. Because social media makes information easily accessible, some people or organizations distribute false news for political or commercial gain. This news may influence elections and attitudes. Even though English fake news is widely detected and limited, Arabic fake news is hard to recognize owing to a lack of study and data collection. Wara Arabic bidirectional encoder representations from transformers (WaraBERT), a hybrid feature extraction approach, combines word level tokenization with two Arabic bidirectional encoder representations from transformers (AraBERT) variants to provide varied features. The study also discusses eliminating stopwords, punctuations, and tanween markings from Arabic data. This study employed two datasets. The first, Arabic fake news dataset (AFND), has 606,912 records. Second dataset Arabic news (AraNews) has 123,219 entries. WaraBERT-V1 obtained 93.83% AFND accuracy using the bidirectional long short-term memory (BiLSTM) model. However, the WaraBERT-V2 technique obtained 81.25%, improving detection accuracy above previous researchers for the AraNews dataset. These findings show that WaraBERT outperforms word list techniques (WLT), term frequency-inverse document frequency (TF-IDF), and AraBERT on both datasets.
Volume: 15
Issue: 1
Page: 836-845
Publish at: 2025-02-01

Generic green skills: maturity level of vocational education teachers and students in Indonesia

10.11591/ijere.v14i1.29191
Farid Mutohhari , Putu Sudira , Pardjono Pardjono , Suyitno Suyitno , Warju Warju , Fajar Danur Isnantyo , Nuur Wachid Abdul Majid
Vocational education (VE) is one of the institutions that must answer environmental problems by providing green job skills to its students. However, VE in Indonesia still experience various obstacles in providing this provision, so the aim of this research aims to analyze the extent of the level of green skills (GS) in teachers and students in this country, which includes the dimensions of cognitive, interpersonal and intrapersonal competence as an illustration for developing a priority scale for improvement. In addition, examining the differences and correlations between dimensions and the contribution of dimensions to GS as a whole is an additional goal. The survey method was carried out using a generic GS questionnaire instrument in VE that have Adiwiyata status. Data were analyzed using three stages: descriptive analysis, ANOVA-post hoc Tukey test, and path analysis. As a result, students’ GS still show a low category, while teachers get a high category. Between dimensions show no significant differences. Finally, all competencies have a significant relationship and can construct overall GS. These results indicate that there is still a need to strengthen teacher competencies in GS-based learning management and strengthen collaboration with all levels of society.
Volume: 14
Issue: 1
Page: 179-187
Publish at: 2025-02-01

Online teaching and learning in higher education institution in the Northern Philippines

10.11591/ijere.v14i1.30561
Rashid Ceazar Galanto Ormilla , May Grace Ogano Ongan
The study investigates the shift to online education in the Philippines due to the COVID-19 pandemic and its impact on the education system. Understanding this transition is vital as it signifies a significant adaptation affecting both faculty members and students. Conducted at Ifugao State University, Ifugao, Philippines, we employed a convergent parallel design using online surveys and interviews to determine the perceptions of 30 faculty members and 30 students and their experiences regarding pandemic driven online teaching-learning modes. Findings revealed varied satisfaction levels, with students emphasizing time management and comfort with online technologies for successful learning. The study offers insights into the diverse experiences within the online teaching-learning landscape during the pandemic. It highlights the need for faculty training, flexible class schedules, alternative dissemination methods, and institutional support to enhance online teaching-learning strategies.
Volume: 14
Issue: 1
Page: 505-515
Publish at: 2025-02-01

iFoodAR: augmented reality for high school food design technology

10.11591/ijere.v14i1.29702
Nur Ain Safura Azizoon , Wan Nurlisa Wan Ahmad , Qistina Ahmad Fizal , Tang Jing Rui , Mohd Yusof Kamaruzaman
Technology is advancing with the times. Augmented reality (AR) received great attention in education because it focuses on technology that connects the real and virtual worlds in real-time. The blending of AR technology and educational content aims to generate innovative thinking that can improve the effectiveness of teaching and learning for students in real-life scenarios. This study aimed to develop an AR module and application (apps.) for high school students to learn about food technology. Five phases of the analysis, design, development, implementation, and evaluation (ADDIE) model were used to develop food technology applications in the classroom based on AR technology. An interview was conducted to obtain the usability of the AR module from the selected expert. The results showed that iFoodAR fulfilled the requirement in line with the standard curriculum and assessment document (DSKP) of the Malaysian Ministry of Education and gained positive feedback on using AR in the classroom from the expert teachers. It is concluded that iFoodAR apps have the potential to cater the diversity learning styles, leading to a shift in teaching methods incorporating more interactive and visually stimulating learning experiences.
Volume: 14
Issue: 1
Page: 406-414
Publish at: 2025-02-01
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