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25,002 Article Results

A new enterprise architecture-based approach for smart city value co-creation

10.11591/ijece.v15i1.pp767-782
Meryeme El Houari , M'barek El Haloui , Badia Ettaki
In an era marked by vertiginous technological advancements and urban complexities, digital transformation has emerged to enable cities to offer smart services. This transformation optimizes interaction and collaboration between smart city actors, instead of working in isolated silos. There is a real need for a federative approach that can be aligned with urban vision and goals to support smart city implementation. In this context, enterprise architecture (EA) is emerging as a pivotal force reshaping smart city and supporting its development and transformation. However, the successful implementation of smart city depends also on the collaborative effort to co-create value among city's stakeholders. The present study develops a new approach based on enterprise architecture within the smart city ecosystem. Through methodical delineation our approach seeks to enhance value co-creation, improve smarter service design, and support community engagement.
Volume: 15
Issue: 1
Page: 767-782
Publish at: 2025-02-01

School resilience through quality management in early childhood education: a case study from Indonesia

10.11591/ijere.v14i1.30384
Nurul Arifiyanti , Siti Irene Astuti Dwiningrum , Amir Syamsudin , Harun harun
Poor management of the education system can cause a decrease in school quality. Moreover, the increasing of similar institutions in early childhood education (ECE) in Indonesia gives a school must have good resilience. These institutions must ensure that the educational programs they provide to children are of high quality, thus earning the trust of preschool parents. This article aimed to highlight the importance of paying attention to school management. Therefore, schools that already have good resilience need to be studied to have an impact on schools that are in the stagnant category. The method used was a case study with in-depth interviews. The results indicate that the resilience schools use four strategies to remain resilient. These strategies include having quality human resources, unique school programs, and school promotion. The research results highlight the importance of quality human resource management, superior programs such as foreign language learning and international curricula, and effective promotion in maintaining the resilience of educational institutions amidst competition.
Volume: 14
Issue: 1
Page: 269-278
Publish at: 2025-02-01

Integrated U-Net segmentation and gated recurrent unit classification for accurate brain tumor diagnosis from magnetic resonance imaging images

10.11591/ijece.v15i1.pp1051-1064
Ravikumar Sajjanar , Umesh D. Dixit
Early diagnosis and proper grouping of tumors in the brain are critical for successful therapy and positive outcomes for patients. This work proposes a complete technique for identifying brain tumors that employ sophisticated artificial intelligence methodologies and achieve an accuracy rate of 97.18%. The work makes use of the brain tumor magnetic resonance imaging (MRI) collection in Kaggle, which has 723 MRI scans classified as glioma, meningioma, pituitary tumor, and no tumor. These images are initially preprocessed, which includes scaling to a homogeneous size normalizing, and removal of noise to ensure uniformity and clarity. To improve the information set, generative adversarial networks (GANs) are used to perform data augmentation, producing artificial pictures that improve the database variety and resilience. To achieve exact cancer localization, the U-Net construction, recognized for its encoder-decoder design and skip links, is used to divide up tumor areas across images generated by MRI. The image segments are then input into gated recurrent units (GRUs), to analyze a collection of features to capture periods and differences between segments. The last classification is accomplished using an entirely linked layer and then a softmax stimulation, which provides the tumors classes. This method helps for medical experiments and clinical methods.
Volume: 15
Issue: 1
Page: 1051-1064
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

Strategies for students’ well-being development: the task-oriented classroom approach

10.11591/ijere.v14i1.30158
Esa Nur Wahyuni , Ali Maksum , Rahmat Aziz , Retno Mangestuti
Promoting students’ well-being is a vital aspect of education. Creating a conducive classroom learning environment is essential, and task orientation plays a significant role. This paper aims to explore three research objectives related to the influence of the learning environment on student well-being by focusing on creating a task-oriented learning environment. The study employs a quantitative approach with a cross-sectional study design. The study analyzed 1,698 students (676 male and 994 female students) from nine cities in East Java, Indonesia. The results of the simultaneous regression analysis showed that R=.578, R2=.334, and p<.10. The learning environment was found to predict student well-being by 33.4% significantly. At the same time, task orientation was identified as the most dominant factor affecting student well-being. The study’s findings suggest that task orientation could be a solution to enhance student well-being in classroom learning practices. This study suggests the need for teacher development to improve teachers’ professional ability to facilitate learning in the classroom. Future research should consider using central variables, including moderating and intervening variables, to explore the relationship between the learning environment and student well-being.
Volume: 14
Issue: 1
Page: 535-543
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

Enhancing listening skills: issues and possible solutions

10.11591/ijere.v14i1.30226
Gjinali Aida , Naqo Eliona
The paper aims to investigate the extent to which listening skills development is realized in Italian language classes in Albanian pre-university education as one of the basic skills naturally interconnected comprehension and production. The research at hand is the first of this nature conducted in Albanian schools. The issues encountered in the development of this skill have been verified in our teaching experience; It has been noticed that students enrolled in the first-year encounter difficulties related to listening skills. Therefore, this study was considered as important and the relevant questionnaires were compiled. Following the collection of information, its analysis, and interpretation, possible suggestions were sought considering the encountered issues. The study revealed that this skill is underutilized or not utilized properly, as it is often not considered as a required skill. Students are limited to reading or listening skills only, delivered either by the teachers in class or through the few exercises provided by the foreign language book, without employing various strategies or techniques for its development and without using relevant authentic materials.
Volume: 14
Issue: 1
Page: 516-524
Publish at: 2025-02-01

Specifics of population psychodiagnostics on the example of Kazakhstan, China, and Japan: a comparative analysis

10.11591/ijere.v14i1.30363
Aigerim Mynbayeva , Mi Zhou , Gulsharat Minazheva , Zharas Seiitnur
This research aimed at analyzing the history of psychological testing in three Asian countries (Kazakhstan, China, and Japan) in a comparative chronological aspect. A modern trend of interest in population psychodiagnostics was examined, considering a sample of university professors from the studied countries. The study had two stages: theoretical (cross-cultural analysis of the chronological development of psychodiagnostics in three countries) and experimental (in-depth interviews with professors). The study population was 72 respondents. As a result, two periods of psychodiagnostics were distinguished in each country: prescientific and scientific. The general factors influencing the historical development of psychological testing were: i) country’s history and influence of wartime; ii) positive and negative influence of ideology (communist and capitalist) on the psychometrics’ development; iii) the history of psychology and testing in particular, its methodology and methods; iv) the emergence of regional trends in the cooperation and countries’ level of publicity. Consequently, based on the interview, the testing of career interests and individual career guidance significantly dominated in China (4.8) while in Japan it was testing of interpersonal relationships (4.9). The present study may be in demand in future research to develop specific questionnaires and methods for studying the population considering national and historical characteristics.
Volume: 14
Issue: 1
Page: 240-249
Publish at: 2025-02-01

Perceive social support, academic self-efficacy, and learning engagement among high school students in China

10.11591/ijere.v14i1.31029
Liu Yang , Lim Hooi Lian
The aim of this study was to analyze the mediating role of academic self-efficacy in the relationship between perceive social support and learning engagement among Chinese senior high school students. A quantitative research method was adopted, and 572 Chinese senior high school students from Inner Mongolia Autonomous Region in China completed three self-report questionnaires. Correlation analysis revealed that senior high school students perceive social support, academic self-efficacy, and learning engagement were significantly correlated with each other. In addition, structural equation modeling analysis showed that perceive social support exerted its indirect effect on learning engagement through the mediation of academic self-efficacy. These findings have practical implication for government policymakers, education administrators, teachers, students, and parents, informing evidence-based policies, interventions, and strategies to enhance learning engagement and academic success.
Volume: 14
Issue: 1
Page: 629-635
Publish at: 2025-02-01

Malay essay writing module based on thematic approach for non-native speaker: a need analysis in primary schools

10.11591/ijere.v14i1.31040
Edmund Austrus , Zamri Mahamod , Nor Hafizah Adnan
The challenges faced by non-native speaking pupils in primary schools, characterized by diverse backgrounds, highlight the difficulty in teaching and learning essay writing. This study was conducted to identify the needs for the development of a Malay language essay writing module based on a thematic approach through the needs analysis phase. This qualitative study was conducted among Malay language teachers in Sarawak. Eight teachers were purposively sampled, and thematic analysis was employed for data analysis. The findings found that there are six themes that have been identified, namely: i) relevant form of teaching and learning in essay writing; ii) relevant teaching and learning resources; iii) relevant teaching and learning activities; iv) relevant teaching and learning strategies; and v) the needs of the thematic approach in essay writing; vi) the needs for the development of thematic-based essay writing module. The findings underscore the imperative development of a Malay essay writing module based on a thematic approach to enhance the essay writing proficiency of non-native-speaking pupils. Furthermore, the study's insights offer valuable guidance for researchers in designing and developing modules during the subsequent phases, contributing to the refinement of essay writing pedagogy in primary schools.
Volume: 14
Issue: 1
Page: 103-113
Publish at: 2025-02-01

Unraveling social and economic problems: what basics of critical thinking skills are needed?

10.11591/ijere.v14i1.29180
Wiwik Sri Utami , Kusaeri Kusaeri , Ali Ridho , Ahmad Yusuf , Bambang Sigit Widodo , Hendri Prastiyono , Sri Murtini
Equipping knowledge and developing critical thinking skills about social and economic issues to students is important. This study aimed to analyze the ability of prospective students of Islamic State of Madrasah of Insan Cendekia (ISM-IC) to think critically about socioeconomic problems. This research reveals a critical thinking skills gap among prospective students of Madrasah Tsanawiyah/Islamic Junior High School (IJHS) and non-IJHS who participated in the national selection of new students (NSoNS). This study uses a cross-sectional survey approach with standard instruments from the NSoNS ISM-IC. Data was obtained from 1,832 participants in the social sciences group test, consisting of 1,197 people from IJHS and 635 from non-IJHS. Data analysis using R Programming, package ‘ggstatsplot’, and via Microsoft Excel. The result is: i) a gap in social studies scores between IJHS and non-IJHS students of -0.215, with the social studies scores of IJHS students lower than non-IJHS; ii) critical thinking skills are proven to have a very real impact on the occurrence of social studies score gaps, through the inability of students to answer the higher-order thinking skills (HOTs) category questions. This finding indicates the urgency of the education unit to provide nuanced literacy models and learning and HOTs to increase think of critic ability about socioeconomic matter.
Volume: 14
Issue: 1
Page: 566-574
Publish at: 2025-02-01

Hybrid long short-term memory and decision tree model for optimizing patient volume predictions in emergency departments

10.11591/ijece.v15i1.pp669-676
Ahmed Abatal , Mourad Mzili , Zakaria Benlalia , Hajar Khallouki , Toufik Mzili , Mohammed El Kaim Billah , Laith Abualigah
In this study, we address critical operational inefficiencies in emergency departments (EDs) by developing a hybrid predictive model that integrates long short-term memory (LSTM) networks with decision trees (DT). This model significantly enhances the prediction of patient volumes, a key factor in reducing wait times, optimizing resource allocation, and improving overall service quality in hospitals. By accurately forecasting the number of incoming patients, our model facilitates the efficient distribution of both human and material resources, tailored specifically to anticipated demand. Furthermore, this predictive accuracy ensures that EDs can maintain high service standards even during peak times, ultimately leading to better patient outcomes and more effective use of healthcare facilities. This paper demonstrates how advanced data analytics can be leveraged to solve some of the most pressing challenges faced by emergency medical services today.
Volume: 15
Issue: 1
Page: 669-676
Publish at: 2025-02-01

A systematic review of the changes, challenges, and implications of China’s teacher education policies (2012 to 2023)

10.11591/ijere.v14i1.29770
Huang Zhi , Latha Ravindran , Mansour Amini
Although China’s teacher education policies have achieved significant progress in improving teacher quality, they have also undergone substantial changes and encountered new challenges. It is necessary to systematically analyze policies from the past decade to achieve a prudent balance between the immediacy and foresight of policymaking. This systematic analysis paper examines China’s teacher education policies from 2012 to 2023, reviewing relevant policy documents from authoritative sources. The study reveals a strategic shift towards fostering comprehensive and innovative teacher talent, promoting professional development, and addressing urbanrural education disparities. Emphasis is placed on strengthening professional ethics and creating a societal atmosphere of respect for teachers. However, challenges arise, including the “de-normalization” of teacher education in higher education institutions, regional disparities in teacher resources, and issues in in-service teacher education. These findings have profound implications for the future of teacher education policies, both within China and globally. They underscore the need for ongoing policy review and adaptation, the importance of balance between research and teaching in teacher education programs, and the need for a more integrated and streamlined approach to in-service teacher education and professional development. The study provides insights for policy development in the field of teacher education.
Volume: 14
Issue: 1
Page: 207-221
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 mediating effect of study habits between parental involvement and algebraic problem-solving achievement

10.11591/ijere.v14i1.29941
Imdad Ali , Samiran Das
Algebra is the major branch of mathematics that deals with numbers, and symbols are mostly used in problem-solving. Students often struggle to learn mathematics due to the difficulties of solving algebraic problems at the secondary level. Several factors affect student problem-solving achievement (PSA). The present study aims to examine the mediating effect of study habits (SH) in the relationship between parental involvement (PI) and algebraic PSA. For this purpose, a study habits scale and a parental involvement scale are used, and a problem-solving test is done for algebraic problem-solving. In this correlational study, Baron and Kenny’s series of regression models is used to test the mediating effect of SH. The findings revealed that that PI, SH and algebraic PSA are positively correlated. Also, it is confirmed that SH mediates the relationship between PI and algebraic PSA because there is no longer any significant effect of PI on PSA after SH is included in the model. It is recommended that students’ problem-solving skills be developed through their better study habits. Increasing parental support may promote students better SH, which in turn better achievement in problem-solving. Parents and teachers should monitor and encourage students’ study habits for better performance in problem-solving and mathematics as a whole.
Volume: 14
Issue: 1
Page: 583-588
Publish at: 2025-02-01
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