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FGMPSO: a hybrid firefly-gradient-MOPSO framework for high-dimensional feature selection

10.11591/ijeecs.v41.i3.pp1082-1094
Alwatben Batoul Rashed
When working with high-dimensional datasets, selecting the most relevant features is essential for improving both model clarity and processing efficiency, all while keeping predictive accuracy intact. In response to this challenge, the study introduces firefly-gradient-multi-objective particle swarm optimization (FGMPSO), an advanced hybrid technique that blends the firefly algorithm, gradient descent (GD), and multi-objective particle swarm optimization (MOPSO). This approach is specifically designed to identify an optimal subset of features that balances dimensionality reduction with strong classification performance. The method was evaluated on eight benchmark datasets and compared against multiple PSO-based feature selection techniques. The empirical results demonstrated that FGMPSO consistently achieved superior or competitive classification accuracy while selecting significantly fewer features. Notably, in several datasets, FGMPSO not only reduced dimensionality but also outperformed other methods in terms of classification accuracy. This efficiency is attributed to the intelligent exploration of the search space by the firefly algorithm, refinement via GD, and effective trade-off optimization enabled by MOPSO. The findings suggest that FGMPSO is a robust and scalable solution for feature selection, particularly suitable for complex and high-dimensional datasets. Its adaptability, convergence speed, and balance between dimensionality reduction and accuracy position it as a valuable tool in modern machine learning pipelines.
Volume: 41
Issue: 3
Page: 1082-1094
Publish at: 2026-03-10

Ontology-based semantic link prediction for enhancing academic collaboration through knowledge management

10.11591/ijeecs.v41.i3.pp1040-1048
Pham Thi Thu Thuy , Thinh Thi Thuy
This paper introduces a novel ontology-based semantic link prediction framework that unifies structural, temporal, and semantic signals from heterogeneous scholarly sources to enhance academic collaboration forecasting. By integrating AMiner, DBLP, and Mendeley datasets into a unified SKOS- and Dublin Core-aligned ontology, the framework enables semantic enrichment, cross-source reasoning, and contextualized link prediction. Unlike previous studies that focus solely on structural features or basic content similarity, our approach leverages ontology-based semantic feature engineering and graph-based learning for robust and interpretable predictions. Experimental results show that random forest and graph neural networks significantly outperform traditional models, achieving high accuracy and ranking precision. This work contributes to knowledge management by enabling expert recommendation, trend identification, and semantic integration for strategic academic planning.
Volume: 41
Issue: 3
Page: 1040-1048
Publish at: 2026-03-10

Classification of DoS/distributed DoS threats in software defined networks using advanced deep belief network-long short term memory architecture

10.11591/ijeecs.v41.i3.pp1000-1016
Manjula Maraiah , Venkatesh Venkatesh
With the evolution of telecommunication core and access networks, the next generation networks leverages software defined networks (SDN) to provide flexi bility, scalability and centralized control. Denial of service (DoS)/distributed DoS (DDoS) attacks have been a major threat to next generation networks especially to the centralized architecture of SDNs. The ever-changing and dynamic nature of the DoS/DDoS attacks makes it challenging to detect and resolve them. The existing models to handle DoS/DDoS attacks often suffer from false positive rates and adaptability. In order to solve these problems, this study aims to create and apply sophisticated deep learning framework namely adversarial DBN-LSTM to accurately detect and classify various DoS/DDoS attack types. The proposed adversarial DBN-LSTM model is based on the generative adversarial networks. The proposed model uses generator to generate the adversarial attack and discrim inator to detect the attacks. The adversarial DBN-LSTM model is evaluated using a dataset specifically generated in a Mininet-based SDN controller environment to ensure relevance and practical applicability. The performance of the adver sarial DBN-LSTM is compared with other prevalent models. The adversarial DBN-LSTMmodelachieves accuracy about 99.4%. The proposed work achieves a breakthrough in identifying and preventing DoS/DDoS threats in relation to SDNenvironment.
Volume: 41
Issue: 3
Page: 1000-1016
Publish at: 2026-03-10

Design and implementation of novel encryption architecture using mix column with novel adder

10.11591/ijeecs.v41.i3.pp1134-1140
Radha Appisetty , Munuswamy Siva Kumar
Digital information is extremely simple to process these days, but it can be accessed by unauthorized people. Cryptography is one of the most effective and widely used methods for data security, to protect this information. The cryptography techniques are becoming popular and widely adopted due to the security threats during data transmission. An essential part of a cryptographic system, cryptography algorithms are developed and implemented to increase data security. The developers of these cryptographic algorithms took into consideration additional parameters, including speed, resource consumption, reliability, usage type, and flexibility, even if their primary goals are confidentiality, integrity, and authenticity. It’s important to understand that each component affects the way that a cryptographic technique is designed. Hence, this analysis presents the design and implementation of a novel encryption architecture using mix column with a novel adder. The novel encryption algorithm is designed for an encryption architecture (EA) with mix column using novel adder. This novel encryption algorithm will attain better security and performance.
Volume: 41
Issue: 3
Page: 1134-1140
Publish at: 2026-03-10

A smart-contract framework for patient identity management in digital health platforms

10.11591/ijeecs.v41.i3.pp1025-1039
Cahyo Prihantoro , Dany Candra Febrianto , Maie Istighosah , Ahmad Uffi Lestrasi Ma’ruf , Angger Taufiqur Rohman Winarno , Yudha Islami Sulistya
Asmart-contract framework for patient identity management in digital health platforms. A major gap in current digital health ecosystems is the absence of a portable and verifiable patient identity layer across fragmented electronic health record (EHR) systems. The problem addressed is the lack of a portable, verifiable, and patient-centric identity layer across fragmented electronic health record systems, which weakens access accountability and privacy. The proposed solution couples fast healthcare interoperability resources (FHIR) with self-sovereign identity (SSI), storing FHIR payloads off-chain in the InterPlanetary file system (IPFS) and committing only encrypted pointers and policies on Polygon smart contracts. Patient identifiers and content addresses are protected with AES-256 GCMauthenticated encryption and elliptic-curve key wrapping (ECIES) for both the healthcare administrator and the patient. A web implementation in Next.js using thirdweb automates wallet creation, keystore handling, encryption, and on-chain commits. In evaluation with 50 synthetic registrations, success reached 100 percent, median end-to-end latency was 5.86 seconds, mean on-chain latency 3.77 seconds, average transaction fee 0.0401 POL/MATIC, encryption time 13.9 milliseconds, and all decryptions validated. The results indicate practical feasibility for portable identity and auditable access, with on-chain latency as the main bottleneck to be reduced through batching, cheaper layers, and broader field trials. However, this study is limited because the evaluation uses only synthetic data and singleprovider testing, without real-world patients or multi-institutional environments. Zero-knowledge proofs (ZKP) are discussed conceptually as future integration and are not implemented or benchmarked in this work.
Volume: 41
Issue: 3
Page: 1025-1039
Publish at: 2026-03-10

Enhanced prediction of chronic kidney disease onset through machine learning techniques

10.11591/ijeecs.v41.i3.pp966-976
Samuel John Parreño , Maria Cristine Joy Anter
Chronic kidney disease (CKD) is a global health concern that often progresses silently to severe complications. This study aims to enhance CKD prediction using machine learning models: support vector machines (SVM), extreme gradient boosting (XGBoost), k-nearest neighbors (k-NN), and a stacking model. The dataset, sourced from the UCI machine learning repository, includes clinical and demographic attributes from 200 patients. After preprocessing, the final dataset comprised 161 samples and 143 features. SVM achieved perfect classification performance with 100% accuracy, precision, and recall. XGBoost followed closely with an accuracy of 97.44% and a kappa statistic of 0.9451. The k-NN model delivered strong performance, achieving 92.31% accuracy. The stacking model outperformed all individual models, achieving perfect accuracy. The models demonstrated high sensitivity and specificity, indicating their effectiveness in distinguishing CKD from non-CKD cases. These findings emphasize the potential of machine learning in CKD diagnosis. Early detection can lead to improved clinical outcomes by enabling timely interventions and personalized treatment strategies. Future research should emphasize comprehensive feature engineering and larger, more diverse datasets to improve predictive accuracy and generalizability. Incorporating machine learning models in nephrology could significantly advance CKD detection and management.
Volume: 41
Issue: 3
Page: 966-976
Publish at: 2026-03-10

Thermal effects of curing parameters on the natural frequency of GNP/Ag ink composites

10.11591/ijeecs.v41.i3.pp845-858
Khirwizam Md Hkhir , Nor Azmmi Masripan , Cholatee Photong , Alan Watson , Mohd Azli Salim
This research examines how curing temperature and duration influence the electrical and mechanical behavior of hybrid graphene nanoplatelet and silver (GNP/Ag) conductive ink. The ink was formulated from GNPs, silver flakes and silver acetate printed on copper substrates, then cured 240 °C, 250 °C, and 260 °C for one to three hours. Electrical resistance was measured using a Two-Point probe, while natural frequency was obtained from experimental modal analysis (EMA) on stainless-steel (SUS304) cantilever beams laminated with printed ink. The results show that the higher curing temperature and longer curing time reduce resistivity and increase natural frequency, with the best performance observed at 260 °C for 3 hours (8.4×10⁻⁶ Ω.m and a 4.2 Hz increase). These findings confirm that a direct relationship between conductivity and stiffness, where conditions that promote stronger particle bonding also raise structural rigidity. The main contribution of this research is the joint evaluation of curing effects on both electrical and vibrational responses, offering a combined electro-mechanical perspective that is not often explored in GNP/Ag ink research. The results provide practical guidance for selecting curing conditions based on the required balance between conductivity and mechanical stability in flexible and stretchable electronic applications.
Volume: 41
Issue: 3
Page: 845-858
Publish at: 2026-03-10

Arich and balanced phonetics corpus for modern standard Arabic ASR systems

10.11591/ijeecs.v41.i3.pp1049-1059
Youssef Boutazart , Naouar Laaïdi , Abderrahim Ezzine , Hassan Satori , Mohamed Taj Bennani
This research delves into the creation of an innovative Modern Standard Ara bic corpus, aiming for a comprehensive balance and richness while adhering to Zipf’s law. Building a phonetically diverse Arabic sentence collection yields significant advantages in terms of efficiency, cost-effectiveness, and storage ca pacity compared to conventional corpora. The corpus undergoes meticulous seg mentation into graphemes, which are then manually converted into phonemes, resulting in a total of 19769 phonemic units. Among these phonemes, conso nants like ’Laam- l’ account for 10%, while ’Fatha- A’ vowels constitute 20%. Evaluation of this corpus using an automatic speech recognition (ASR) system reveals a sentence error rate (SER) of 30% and a word error rate (WER) of 15%. Furthermore, statistical analysis unveils that diacritic marks encompass 47.59% of the corpus, with graphemes comprising the remaining 52.41%. These dia critized marks provide valuable insights into the precise phonetic transcription of the corpus. Additionally, the study provides detailed breakdowns of consonants based on their place and manner of articulation, enhancing our understanding of phonetic structures.
Volume: 41
Issue: 3
Page: 1049-1059
Publish at: 2026-03-10

Spatial analysis of stunting risk factors in Central Java, Indonesia: A geographically weighted regression approach (2023 data)

10.11591/ijphs.v15i1.26881
Sylvia Anjani , Faik Agiwahyuanto , Maulana Tomy Abiyasa
The 2022 Indonesian Nutritional Status Survey (SSGI) reported a stunting prevalence of 20.8% in Central Java. Although various studies have examined its risk factors, few have applied a spatial perspective. This study aims to analyze regional variations in stunting risk factors and their contribution to rising stunting rates. This is a quantitative explanatory study employing the geographically weighted regression (GWR) method. Secondary data were obtained from the Central Java Health Profile and Badan Pusat Statistik Indonesia (BPS) in 2023, using a total sampling of 35 districts/cities. The GWR results indicated that chronic energy deficiency (CED; β = 0.0014, p = 0.068) and exclusive breastfeeding (β = 0.0791, p = 0.087) were marginally positively associated with stunting. Low birth weight (LBW) showed a significant positive association (β = 0.1009, p = 0.041), while access to improved sanitation had a strong negative effect (β = -0.1882, p = 0.004). Iron supplementation (≥90 tablets) was not significant (β = -0.0629, p = 0.134), whereas access to improved drinking water was positively and significantly correlated with stunting (β = 0.3778, p = 0.028). These findings contradict existing theories, particularly where higher rates of exclusive breastfeeding and access to clean water are unexpectedly associated with increased stunting in several regions. This suggests the need for further in-depth investigation in those areas to better understand the underlying factors.
Volume: 15
Issue: 1
Page: 179-189
Publish at: 2026-03-05

Workplace spirituality and nurses’ well-being: integrative review (2015-2025)

10.11591/ijphs.v15i1.26888
M. Fahrin Azhari , Johari Daud Makajil , Fredie Robinson , Muthmainnah Muthmainnah , Dwi Agustina , Winda Maolinda
Occupational well-being and workforce sustainability in post-pandemic healthcare systems are at risk due to increasing emotional, ethical, and workload-related stressors that nurses encounter. Workplace spirituality has also been suggested as a protective factor, but empirical research remains fragmented and insufficiently synthesized. This integrative review aimed to synthesize the recent evidence on the role of workplace spirituality in the occupational well-being of nurses. A systematic search of Scopus, MEDLINE, and Cochrane databases identified English-language quantitative studies published between 2015 and 2025. Nineteen studies met the inclusion criteria and were synthesized using Whittemore and Knafl integrative review framework, with reporting relying on PRISMA 2020. There were five themes that included i) spirituality and burnout reduction, ii) organizational commitment and retention, iii) work engagement and job satisfaction, iv) spiritual congruence and interpersonal care, and v) spiritual leadership and well-being. Most findings demonstrated moderate-to-strong associations between workplace spirituality and decreased burnout, increased engagement, and greater organizational commitment. Nevertheless, these advantages were conditional and mitigated in the conditions of overwork, insufficiency of staffing, moral tension, and insufficient organizational support. This review offers a quantitative integrative synthesis of the first nursing-specific evidence to be published after the pandemic and shows that workplace spirituality serves as a complementary resource, rather than a standalone, to occupational well-being. The findings highlight important implications of nursing policy regarding introducing spirituality-based leadership development, ethical governance, and workforce support as part of the broader structural reforms.
Volume: 15
Issue: 1
Page: 160-170
Publish at: 2026-03-05

Sex differences on patient safety culture practices among nurses in Karawang, Indonesia: a cross-sectional study

10.11591/ijphs.v15i1.22681
Lilis Suryani , Santhna Letchmi , Faridah Mohd Said
Nurses are critical in enhancing the quality of care and patient safety due to their commitment to caring for patients 24 hours a day and their interaction with families and other health professionals. The role of gender in the interprofessional team is more complex and warrants further investigation, even though it has been increasingly studied at the level of the individual healthcare provider. In this study, we examined sex differences in patient safety culture practices among nurses. This study was conducted using a cross-sectional design at a general public hospital in Karawang, West Java, Indonesia. The hospital survey on patient safety culture (HSPSC) was used. A chi-square test and an independent t-test were used to determine whether there were any differences in patient safety culture practice between the sexes. A total of 75 males and 145 females agreed to join this study. The mean age of female and male participants was 34.21 ± 14.07 and 36.29 ± 12.51 years old, respectively. Age, marital status, and working position were significantly different between males and females (p < 0.05). Females reported to have a higher overall score of patient safety culture practices than males (3.65 (SD = 1.12 vs. 3.11 (SD = 1.43), p-value = 0.001). According to the patient safety culture practice domain, teamwork (4.21 (SD = 1.35) vs. 3.78 (SD = 1.76), p-value = 0.001), response to error (3.56 (SD = 1.93) vs. 3.31 (SD = 1.93), p-value = 0.001), and communication openness (3.881.56 vs. 2.35 (SD = 0.92), p-value = 0.001) were higher among female than male. Nurses must be trained, and professional communication must be improved as a means of ensuring better patient safety. Patient safety cultures vary widely across hospitals, units, and countries, as evidenced by the growing number of studies that have looked at this issue in depth.
Volume: 15
Issue: 1
Page: 126-131
Publish at: 2026-03-05

Calgary family intervention model enhances dietary compliance and knowledge in T2DM patient

10.11591/ijphs.v15i1.26901
Muhtar Muhtar , Aniharyati Aniharyati , Julhana Julhana , Fadlurahmi Fadlurahmi , Muhammad Arifki Zainaro , Martiningsih Martiningsih
The urgency was in developing a more holistic and sustainable approach to supporting type 2 diabetes mellitus (T2DM) patients. This study evaluated the effectiveness of the Calgary Family Intervention Model (CFIM) in improving dietary adherence and knowledge in patients with T2DM. This study used a quantitative method with a quasi-experimental design, involving 280 patients with type 2 diabetes mellitus at the Bolo Community Health Center from January to October 2025. The sample was divided into two groups: intervention (CFIM education) and control (booklet). Data were collected using a valid and reliable questionnaire to measure knowledge and dietary adherence. Data analysis was performed using the Wilcoxon and Mann-Whitney tests. The analysis showed significant results, with the mean knowledge score in the intervention group increasing from 4.84±1.235 to 8.98±2.851 (p < 0.05), while in the control group, it increased from 4.64±1.120 to 7.06±1.219. For dietary adherence, the intervention group showed an increase from 27.00±6.518 to 61.38±7.171 (p = 0.000), compared to the control group, which increased from 27.28±5.592 to 49.44±10.194(p < 0.05). The implications of these results have the potential to strengthen the family-based health intervention model and improve the overall well-being of T2DM patients. This study contributes significantly to family nursing practice by demonstrating the efficacy of the CFIM in enhancing dietary adherence and knowledge among patients with T2DM.
Volume: 15
Issue: 1
Page: 150-159
Publish at: 2026-03-05

Compulsive buying behavior and self-esteem among K-pop fan undergraduate medical students in Jakarta

10.11591/ijphs.v15i1.26821
Julia Rahadian Tanjung , Heunice Precious , Mariani Santosa
The rising popularity of K-pop has attracted many teenagers and young adults. Fans tend to purchase idol merchandise as a sign of support and affection, which can lead to compulsive buying behavior. Compulsive buying behavior is one of the coping mechanisms for low self-esteem. This study aimed to investigate the relationship between self-esteem and compulsive buying behavior among undergraduate medical students in Jakarta who are fans of K-pop. A cross-sectional study was conducted involving 97 students, aged 18 to 25, from various medical schools in Jakarta who were actively engaged as members of a K-pop fan club. Data were obtained through the Revised Edwards Compulsive Buying Scale (ECBS-R) and the Rosenberg self-esteem Scale questionnaire. Among the 97 respondents, 35.1% with low self-esteem, and 51.6% with compulsive buying behavior. A significant relationship was found between self-esteem and compulsive buying behavior (p = 0.014). In conclusion, low self-esteem is associated with compulsive buying behavior among K-pop fan medical students, particularly females, which may adversely impact their academic performance.
Volume: 15
Issue: 1
Page: 224-231
Publish at: 2026-03-05

Strengthening intensive care training in response to COVID-19: lessons for medical education

10.11591/ijphs.v15i1.22918
Mochamat Helmi , Djayanti Sari , Yenny Sulistyowati , Andreasta Meliala , Tjahja Nurrobi , Tugas Ratmono , Laksono Trisnantoro
Frequent updates to clinical guidelines during the COVID-19 pandemic have posed significant challenges for audit processes, quality improvement, and the preparedness of healthcare professionals, particularly in intensive care settings. This study aimed to explore the impact of COVID-19-related demands on medical education and training from the perspective of healthcare teams working in intensive care units (ICUs) in Indonesia during the first wave of the pandemic. A qualitative design was employed using semi-structured interviews and focus group discussions with medical personnel directly involved in the care of COVID-19 patients at national referral hospitals. Purposive sampling was applied to recruit participants, including general practitioners, interns, residents, anesthesiologists, and ICU consultants. A total of 66 participants were included across eight focus group discussions, each consisting of eight to nine participants. Data collection continued until thematic saturation was achieved. Transcripts were analyzed using content analysis to identify key themes and subthemes. The analysis revealed five major themes: i) the need for continuous upgrading of knowledge and competencies, ii) the importance of innovative education and training approaches, iii) the role of professional organizations, iv) challenges encountered during training implementation, and v) time constraints. These findings highlight the urgent need for adaptive, continuous, and technology-supported training strategies to strengthen intensive care workforce preparedness during public health emergencies.
Volume: 15
Issue: 1
Page: 23-31
Publish at: 2026-03-05

Comparative assessment of knowledge, attitude, and practice toward self-medication among health and non-health students at Daffodil International University, Dhaka (2022–2023)

10.11591/ijphs.v15i1.26866
Md. Mizanur Rahman , Md. Jahir Alam , Ms Tamanna Khatun , Chaity Sutar , Shabnaz Akter , As-Ad Din Mahmood , Sher Mostafa Sadiq Khan
Self-medication, a popular self-care practice, is common throughout the world and is responsible for serious health complications. The present investigation assessed the knowledge, attitudes, and practices of self-medication among healthcare and non-healthcare students at Daffodil International University, Savar, Dhaka, Bangladesh. A cross-sectional survey of 240 students from the Pharmacy and Environmental Science Departments, ages 19 to 24, was carried out between October 2022 and January 2023. Socio-demographics, knowledge, attitudes, information sources, common medications, and diseases treated were all covered in the pre-tested questionnaire used to gather data. SPSS v16.0 with correlations and descriptive statistics was used for the analysis. Among 240 participants, 50.8% were health science students and 49.2% were non-health science students; 45.8% were male, and 54.2% were female. Most (74.2%, p < 0.01) were aged 21-22 years, mainly in the 4th year (43.3%, p < 0.001). Knowledge analysis showed 37.5% knew over-the-counter (OTC) drugs (p < 0.001) and 55% supported self-medication for minor illness. Common conditions treated were headache (49.2%), fever (23.3%), and cold (16.7%). Painkillers were the most used drugs (39.2%), with family members as the main source of advice (50%). Knowledge had a significant correlation with health science students (p < 0.001). Attitudes revealed 70% used self-medication in the last 6 months; 67.5% discouraged peers, 55.8% reused prescriptions, 73.3% read leaflets, and 61.2% consulted doctors for adverse effects. Previous experiences (74.2%) were the main reason for self-medication. Self-medication is widespread among university students. Health science students demonstrated better knowledge and awareness against self medication while contrasted to non-healthcare students. Awareness programs are needed for all groups.
Volume: 15
Issue: 1
Page: 266-273
Publish at: 2026-03-05
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