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Exploring the effectiveness of multiclass decision jungle for internet of things security

10.11591/ijece.v15i3.pp3095-3106
Smitha Rajagopal , Abhik Sarkar , Venkat Narayanan Manjunath
Network intrusion detection systems (NIDS) are vital in protecting computer networks against cyber security incidents. The relationship between NIDS and internet of things (IoT) security is pivotal and NIDS plays a significant role in ensuring the security and reliability of IoT ecosystems. Ensuring the security of IoT devices is critical for several reasons. It helps safeguard sensitive information, guarantees the dependability of crucial infrastructure, meets regulatory obligations, and fosters user confidence. As the IoT ecosystem expands, prioritizing security is essential to minimize risks and maximize the benefits of connected devices. Given the ever-expanding cyber threat landscape, the multiclass classification task is essential to empower the NIDS with an ability to distinguish between various attack patterns in less computational time. The multiclass decision jungle algorithm is investigated to optimize the performance of NIDS. The research has considered permutation feature importance to include only the relevant features from the data. Using a contemporary dataset such as CICIOT 2023, the study has demonstrated an impressive attack detection rate of over 90% for 20 modern attack types. This research has investigated the effectiveness of IoT security measures and its prospective contributions to the field of cyber security.
Volume: 15
Issue: 3
Page: 3095-3106
Publish at: 2025-06-01

Hybrid semantic model based on machine learning for sentiment classification of consumer reviews

10.11591/ijai.v14.i3.pp2001-2011
Palaniraj Rajidurai Parvathy , Nagarajan Mohankumar , Rajendran Shobiga , Gour Sundar Mitra Thakur , Mamatha Bandaru , Velusamy Sujatha , Shanmugam Sujatha
Digital information is regularly produced from a variety of sources, including social media and customer service reviews. For the purpose of increasing customer happiness, this written data must be processed to extract user comments. Consumers typically share comments and thoughts about consumable items, technological goods, and services supplied for payment in the modern period of consumerism with simple access to social networking globe. Each object has a plethora of remarks or thoughts that demand special attention due to their sentimental worth, especially in the written portions. The goal of the current project is to do sentiment prediction on the Amazon Electronics, Kindle, and Gift Card datasets. In order to predict sentiment and evaluate utilizing many executions evaluates admitting accuracy, recall, and F1-score, a hybrid soft voting ensemble method that combines lexical and ensemble methodologies is proposed in this study. In addition to calculating a subjectivity score and sentiment score, this study also suggests a non-interpretive sentiment class label that may be used to assess the sign of the evaluations applying suggested method for sentiment categorization. The effectiveness of our suggested ensemble model is examined using datasets from Amazon customer product reviews, and we found an improvement of 2-5% in accuracy compared to the current state-of-the-art ensemble method.
Volume: 14
Issue: 3
Page: 2001-2011
Publish at: 2025-06-01

A prediction of coconut and coconut leaf disease using MobileNetV2 based classification

10.11591/ijece.v15i3.pp2834-2844
Kavitha Magadi Gopalakrishna , Raviprakash Madenur Lingaraju
This research is aimed at effectively predicting coconut and coconut leaf disease using enhanced MobileNetV2 and ResNet50 methods. The stages involved in this implemented method are data collection, pre-processing, feature extraction, and classification. At first, data is collected from coconut and coconut leaf datasets. Gaussian filter and data augmentation techniques are applied on these images to eliminate noise during the pre-processing phase. Then, features are extracted using ResNet50 technique, while the diseases are classified using MobileNetV2 approach. In comparison to the existing methods namely, EfficientDet-D2, DL-assisted whitefly detection model (DL-WDM), and modified inception net-based hyper tuning support vector machine (MIN-SVM), the proposed method achieves superior classification values with 99.99% and 99.2% accuracy for coconut leaf and for coconuts, respectively.
Volume: 15
Issue: 3
Page: 2834-2844
Publish at: 2025-06-01

Development and validation of the principals’ digital leadership instrument using Rasch measurement model

10.11591/ijere.v14i3.32214
Peng Yuanyuan , Bity Salwana Alias , Azlin Norhaini Mansor , Mohd Rashid Ab Hamid
This study addresses the critical need for robust measurement tools in digital leadership (DL) within educational settings—a topic of increasing relevance but limited research. Using the Rasch model measurement analysis, the study aims to develop and validate an instrument tailored to assess principals’ digital leadership (PDL) in China. The questionnaire, based on the five dimensions of the International Society for Technology in Education (ISTE) for education leaders—equity and citizenship advocate (ECA), visionary planner (VP), empowering leader (EL), systems designer (SD), and connected learner (CL)—was adapted to reflect Chinese cultural contexts. Following expert validation, the 33-item instrument was piloted with 188 teachers from higher vocational and technical colleges in Sichuan Province. The Rasch analysis, performed using Winsteps 3.72.3, assessed item fit, unidimensionality, local independence, reliability, separation index, and item-person mapping. The findings revealed that 26 items met all assumptions, demonstrating the strong reliability, validity, and psychometric robustness of the instrument. In conclusion, the validated PDL instrument is a reliable tool for assessing the DL of principals within the Chinese educational context, offering insights into professional development, and sets the stage for future research and policy development in the field of educational leadership.
Volume: 14
Issue: 3
Page: 1577-1589
Publish at: 2025-06-01

The effect of psychoeducation on parents of autistic children in Malaysia

10.11591/ijphs.v14i2.24602
Lee Jye Ling , Crendy Tan Yen Teng
Parents have reported a lack of support from professionals in Malaysia, which results in a lack of knowledge in supporting their children, leading to negative attitudes towards their child’s condition, a lack of empowerment, and psychological problems. This study aimed to determine the effect of psychoeducation on the knowledge, attitude, empowerment, and psychological well-being of parents of children with autism spectrum disorder (ASD). The design of this study was true experimental design. The study focused on parents of ASD-diagnosed children aged 2 to 7 years. Nineteen parents participated and were randomly allocated to the intervention group and control group. Pre and post-tests questionnaires assessed knowledge, attitude, psychological well-being, and empowerment. Independent and paired t-tests were used for data analysis. The results showed that there were no significant differences between the control and intervention groups in their knowledge (t (17)=-.186, p=.854), attitude (t(14.9)=1.26, p=.227), psychological wellbeing (t(13.44)=.221, p=.828) and empowerment (t(15.45)=.047, p=.96). There were no significant differences in the pre and post-sessions of the knowledge (t(9)=1, p=.329), attitude (t(9) =.536, p=.605), and psychological well-being (t(9)=.67, p=.521). However, there was a significant difference in the pre and post-session parent’s empowerment (t(9)=-2.5, p=.032). These findings suggest that other interaction factors may affect the effectiveness of psychoeducation sessions in parent’s knowledge, psychological wellbeing, attitude and empowerment.
Volume: 14
Issue: 2
Page: 1060-1067
Publish at: 2025-06-01

Higher education instructors’ and students’ attitudes toward distance learning

10.11591/ijere.v14i3.29383
Yousef M. Arouri , Yousef M. Alshaboul , Diala A. Hamaidi , Asia Y. Alshaboul
This study aimed at exploring the attitudes of higher education instructors and university students regarding distant learning during the COVID-19 epidemic. It took place at a higher education institution of Jordan. Using a mixed method approach, the researchers developed a two-part questionnaire and a semi-structured interview. The questionnaire was distributed questionnaire to 167 instructors and 349 students from the University of Jordan (UJ). The findings showed that the participants have a moderately favorable attitude toward distant learning. Additionally, the findings revealed no statistically significant differences (α=.05) in the attitudes of UJ instructors and students toward distance learning during the COVID-19 pandemic attributedto the study variables. Furthermore, the interviews revealed several themes that the university instructors and students identified as influencing the general effectiveness of their distance learning experience, including access to online platforms and professional training, offering electronic equipment, and protecting the integrity of exams. The study recommends that higher education institutions reconsider the concept of distance learning, considering lessons acquired from the era of compulsory distance learning.
Volume: 14
Issue: 3
Page: 1949-1960
Publish at: 2025-06-01

The effect of family resilience intervention program for caregivers of schizophrenia patient

10.11591/ijphs.v14i2.25029
Puji Lestari , Liyanovitasari Liyanovitasari , Heri Prabowo
Caregivers with schizophrenia face physical, psychological, and financial burdens. Although existing research supports the efficacy of interventions to improve the mental health and wellbeing of caregivers living with schizophrenia patients, there are a number of limitations to the existing evidence. This study aims to assess the effectiveness of a family resilience intervention program for caregivers with schizophrenia using a randomized controlled trial in Central Java, Indonesia. This is a non-blinded study with two parallel arms and an active control group. The intervention group received a combination of face-to-face and interactive online delivery strategies for six weeks. The conner–davidson resilience scale and McMasters family assessment device (FAD) were used to measure study outcomes. The study uses repeated measures analysis of variance, Cohen' d test, and general estimate equations to analyze the data. The study involved over 230 caregivers and found that the family resilience intervention program significantly improved resilience and family functioning scores after the intervention. The study also revealed a moderate effect size on resilience and family functioning. The study suggests that primary healthcare centers should be involved in early detection and monitoring of psychosocial issues within families to maintain and improve their mental health.
Volume: 14
Issue: 2
Page: 709-717
Publish at: 2025-06-01

Optimized wireless power transfer for moving electric vehicles by real-time modification of frequency and estimation of coupling coefficient

10.11591/ijece.v15i3.pp2706-2712
Kazuya Yamaguchi , Haruto Terada , Ryusei Okamura , Kenichi Iida
In order to prevent global warming, electric vehicles are increasingly recommended than gasoline-powered vehicles that have been widely used in the past. However, problems peculiar to electric vehicles exists, and their widespread utilize is not progressing in Japan and other developed countries. This study performed wireless power transfer assuming that electric vehicles are stationary on a road at some distance from an AC power supply. Frequency of a power supply has significant influence on efficiency of wireless power transfer, and it is important to adjust this value on any situation. Therefore, an experiment was conducted based on the optimal frequency expression derived in the past to confirm the correctness of the expression, finally it achieved 60% transport efficiency. Moreover, since the expression includes coupling coefficient between transmission and receiving inductors, its value must be estimated accurately. In this study, an experiment was conducted to estimate value of coupling coefficient using current and voltage values measured from outside circuits, and it was compared with a theoretical expression obtained from laws on electromagnetics.
Volume: 15
Issue: 3
Page: 2706-2712
Publish at: 2025-06-01

Modeling English teachers’ intention to use ICT: technology acceptance and TPACK

10.11591/ijere.v14i3.30444
Li Cao , Mohamad Sattar Rasul , Marlissa Omar , Hutkemri Zulnaidi
Teachers’ acceptance of technology in the teaching setting is significantly influenced by their behavioral intention to utilize information and communication technology (ICT). A considerable amount of study has been done on the use of ICT in teaching English as a foreign language (EFL). Nevertheless, there exists a significant lack of deep studies among EFL teachers in Chinese vocational colleges. Drawing on the technology acceptance model (TAM) and technological pedagogical content knowledge (TPACK) theoretical frameworks, this current study aimed to ascertain whether EFL teachers’ TPACK levels could predict their intention to adopt ICT. A quantitative study was conducted with the participation of 440 EFL instructors from vocational schools in Shandong Province. The seven components met the scale’s validity and reliability requirements and the partial least squares (PLS) approach was utilized to describe the structural model and examine the relationships among significant components. The findings revealed that EFL teachers’ perceived usefulness (PU), perceived ease of use (PEU), and attitudes towards use (ATCU) significantly impacted their behavioral intention to use (BIU) ICT. Moreover, the TPACK framework exerted a substantial influence on their acceptance of ICT. The study’s findings may provide insights and resources for subsequent theoretical research and teaching approaches centered on enhancing the integration of technology in EFL education.
Volume: 14
Issue: 3
Page: 2314-2326
Publish at: 2025-06-01

Enhancing self-care adherence in tuberculosis patients through family support: a systematic review

10.11591/ijphs.v14i2.24749
Miftahul Falah , Tukimin Sansuwito , Regidor III Dioso , Faridah Mohd. Said , Lilis Lismayanti
Tuberculosis (TB) is a persistent and widespread chronic disease, posing a significant global health challenge and ranking as a leading cause of mortality worldwide. Indonesia, in particular, bears the fourth-highest TB burden globally, especially within the South-East Asia (SEA) region. Alarmingly, TB incidence rates increased by 13% from 2020 to 2021. This research utilized a systematic review methodology, sourcing data from four reputable English databases: PubMed, Google Scholar, OpenAlex, and Dimensions. Both quantitative and qualitative studies published in the last five years (2019-2023) were included. A comprehensive search strategy across the specified databases yielded a total of 1,201 articles. These articles underwent meticulous screening, resulting in six articles being deemed relevant for inclusion in the review. The inclusion criteria focused on studies examining the association between family support and self-care adherence among TB patients. The systematic review identified and analyzed these six pertinent articles, highlighting the pivotal role of family support in influencing TB patients’ adherence to self-care during treatment. Enhanced family support was found to correlate positively with improved adherence levels among TB sufferers. In summary, this literature review underscores the critical importance of family support in enhancing self-care adherence for individuals undergoing tuberculosis treatment. The positive correlation between robust family support and improved adherence levels emphasizes the influential role of the family unit in the overall well-being and treatment outcomes of TB patients.
Volume: 14
Issue: 2
Page: 661-671
Publish at: 2025-06-01

Addressing the challenges of overweight and obesity: strategies for promoting a healthier future

https://ijphs.iaescore.com/index.php/IJPHS/article/view/24677
Irfan Chaudhuri , Md. Shahidul Islam
The prevalence of overweight and obesity among over 1 billion people worldwide constitutes a major public health concern. There is an increased risk for the onset of noncommunicable diseases such as type 2 diabetes, cardiovascular diseases, and various types of cancer, while productivity and life quality are diminished. The social, environmental, and behavioral influences on obesity and overweight can be mitigated through targeted interventions, as these conditions are largely avoidable. This study explores the latest findings on the causes, consequences, and remedies for overweight and obesity, with a global perspective. Additionally, it outlines several effective measures and strategies that have been put into place or are being considered in various contexts, including financial constraints, marketing limits, primary healthcare options, and school-based initiatives. To change the obesity epidemic and promote healthy eating and active living for everyone, the research calls for immediate action and a useful strategy that promotes healthy eating and diet, increased physical exercise, and modifications to environmental elements.
Volume: 14
Issue: 2
Page: 936-950
Publish at: 2025-06-01

Body dissatisfaction and body weight status perception among overweight and obese children

10.11591/ijphs.v14i2.25523
Wan Mohd Nurussabah Abdul Karim , Hazizi Abu Saad
Children's perceptions of their weight, body image, and misjudgment of their actual body size can lead to body dissatisfaction, increasing health concerns related to childhood obesity. This cross-sectional study investigated the associations between body dissatisfaction and body weight status (BWS) perception among overweight and obese children aged 10 and 11 years. A total of 398 overweight and obese participants were selected and recruited from eleven primary schools in the state of Kedah, Malaysia. The questionnaire on body image perception was adapted from ‘The seven male and female child figure rating scale,’ and information on BWS perception was collected through a question on how respondents perceived their current BWS. The majority of children (89.4%) desired a smaller body size, and 55.5% did not perceive their BWS correctly; 50% were categorized as “underestimators,” and 5.5% as “overestimators.” There was no significant association between body size discrepancy score and age (p=0.110). However, a significant association was found between the perception of current body image and body mass index (BMI) (p<0.001). The high discrepancies between the perception of current body image and actual weight status need to be addressed, as this misperception could hinder overweight and obese children from successfully achieving a healthy body weight.
Volume: 14
Issue: 2
Page: 869-876
Publish at: 2025-06-01

Managing cooperative learning and digital competences in secondary education: a systematic review

10.11591/ijere.v14i3.30449
Virginia A. Samane-Cutipa , Juan Carlos Callacondo Velarde , Fabian Hugo Rucano Paucar , Fabiola Talavera-Mendoza
The COVID-19 pandemic led most schools to opt for distance education, resulting in challenges in the educational field. However, the increased use of digital technology prompted studies on strategies to help reduce the digital divide concerning two key 21st-century skills: cooperation and digital competencies. This article aims to analyze the study of cooperative learning in relation to the achievement of digital competencies in secondary education. It was developed through a systematic literature review (SLR) using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology, retrieving scientific information from the Web of Science (WoS) and ERIC databases, published from 2018 to 2024. The results and findings emphasize the existence of strategies aimed at improving teaching and learning, academic performance, and students’ communication and social skills through task management, the formation of cooperative teams, and conflict resolution with shared leadership. Additionally, it highlights the development of digital competencies such as information retrieval, digital interaction, virtual object creation, digital security, and responsible citizenship. The conclusions focus on using cooperative learning strategies to make the teacher’s role more efficient in interactive spaces.
Volume: 14
Issue: 3
Page: 2088-2098
Publish at: 2025-06-01

Primary school teachers’ competences in constructing quality multiple-choice questions in Tanzania

10.11591/ijere.v14i3.30825
Florence Kyaruzi , Kingtin Kisamo
Multiple-choice questions (MCQs) are highly used in assessing students’ learning outcomes due to their versatility in promoting test content validity. Nevertheless, teachers experience psychometric challenges in constructing quality MCQs. This study investigated primary school teachers’ competence in constructing quality MCQs in Dar es Salaam Region, Tanzania. Specifically, we examined teachers’ competence in constructing quality MCQs, analyzed the types of item-writing flaws (IWFs) found in teacher-made MCQs, and examined the challenges that teachers encounter in constructing quality MCQs. The study was guided the by classical test theory (CTT) and it employed a mixed-method research approach. In particular, data collection and analysis were conducted using a concurrent triangulation design. A total of 213 MCQs constructed by 20 teachers from ten primary schools were collected and analyzed. The results indicated that primary school teachers were less competent in constructing quality MCQs as 156 (73.2%) of the teacher-made MCQs assessed lower levels of Bloom’s cognitive domain. Similarly, most of the MCQs had IWFs, with 274 (69.2%) having test wiseness flaws and 122 (30.8%) having irrelevant difficulty flaws. The findings call for capacity building to promote teachers’ competence in constructing quality test items.
Volume: 14
Issue: 3
Page: 2051-2060
Publish at: 2025-06-01

An optimized transfer learning-based approach for Crocidolomia pavonana larvae classification

10.11591/ijai.v14.i3.pp2270-2281
Risnawati Risnawati , Rodiah Rodiah , Sarifuddin Madenda , Diana Tri Susetianingtias
The increasing demand for mustard greens has driven farmers to continuously improve mustard greens cultivation. One of the challenges in mustard greens cultivation is the presence of insect pests. A significant pest in mustard greens is Crocidolomia pavonana (C. pavonana). C. pavonana damages plants by feeding on various parts, especially the leaves. The initial step in controlling them is insect pest monitoring. Monitoring aims to establish the control threshold. C. pavonana larvae have four instar stages: instar 1, 2, 3, and 4. Identification of the instar larval stages utilizes deep convolutional neural network (CNN) to classify C. Pavonana larvae on mustard greens using ResNet50V2 and DenseNet169 architectures optimized to enhance classification accuracy. The classification evaluation results show that both DenseNet169 and ResNet50V2 models achieve high accuracy, with DenseNet169 reaching the highest accuracy at 97.1%, while ResNet50V2 achieves an accuracy of 94.2%. The lower loss values on the test data compared to the validation data indicate that the deep learning models have successfully captured the patterns in C. pavonana images for classification. This classification process is expected to be one of the activities in monitoring the instar larvae to improve the accuracy of insecticide spraying and enhance mustard greens production.
Volume: 14
Issue: 3
Page: 2270-2281
Publish at: 2025-06-01
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