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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
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The journal covers all aspects of applied engineering, applied Science and information technology, that is: Engineering: Energy Mechanical Engineering Computing and Artificial Intelligence Applied Biosciences and Bioengineering Environmental and Sustainable Science and Technology Quantum Science and Technology Applied Physics Earth Sciences and Geography Civil Engineering Electrical, Electronics and Communications Engineering Robotics and Automation Marine Engineering Aerospace Science and Engineering Architecture Chemical & Process Structural, Geological & Mining Engineering Industrial Mechanical & Materials Science: Bioscience & Biotechnology Chemistry Food Technology Applied Biosciences and Bioengineering Environmental Health Science Mathematics Statistics Applied Physics Biology Pharmaceutical Science Information Technology: Artificial Intelligence Computer Science Computer Network Data Mining Web Language Programming E-Learning & Multimedia Information System Internet & Mobile Computing Database Data Warehouse Big Data Machine Learning Operating System Algorithm Computer Architecture Computer Security Embedded system Coud Computing Internet of Thing Robotics Computer Hardware Information System Geographical Information System Virtual Reality, Augmented Reality Multimedia Computer Vision Computer Graphics Pattern & Speech Recognition Image processing ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT in education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 73 Documents
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Search results for , issue "Vol 5, No 4 (2025)" : 73 Documents clear
Hybrid Graph Attention Networks for Influencer Ranking in Student Activity Networks Setiawan, Mikhael; Santoso, Ong Hansel; Chandra, Iwan
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1474

Abstract

Detecting influencers in a social network of massive student activities is vital for universities because it will help them understand potential leaders and social behavior. This paper mitigates the issues of classical topology-based metrics by presenting volume calculation through Graph Attention Networks (GATs) applied to a real network with 2,520 students and about 282,000 interactions. A new hybrid method of influencer ranking proposed, which combines the node embeddings obtained by GAT with a structural influence signal from PageRank. The evaluation system includes two main parts. First, qualitative evaluation of the hybrid ranking method against PageRank-only. This assessment learns from a ground truth dataset of 993 formal leaders. Second, evaluate the communities found by GNNs against those discovered by classical methods using internal quality criteria, including modularity and conductance. From the observation, PageRank baseline does slightly better than the hybrid method in ranking and both methods are significantly better from a random rank with their Spearman’s Rank Correlation equal to 0.513 for PageRank based and 0.451 of the hybrid variant, respectively. Yet, in the task of community detection, GNNs have greater representational capacity. Even though the resulting modularity score was also very competitive, communities had much lower (and hence better) average conductance than Louvain and Walktrap methods (0.137 vs 0.198 and 0.302). These paired results shows that: the success of a PageRank baseline is tied to our formal-role-based ground truth which is structural. The GNN’s increased ability to discriminate such well-delineated, socially close communities implies that the embeddings it learns better represent the network’s true social structure. In conclusion, while PageRank effectively reveals the formal leaders in a community, our hybrid GAT technique acts as complement to shed light on emerging influencers.
Development of Application-Based Interactive Learning Media in Automotive Engineering Anwar, Choyrul; Umara, Andi Maga; Nurtanto, Muhammad; Sutrisno, Valiant Lukad Perdana; Nendra, Fadly; Febriyanto, Rusdi
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1538

Abstract

Learning media significantly impacts the effectiveness of the learning process. The automotive industry is experiencing rapid development, resulting in a high demand for technicians with expertise in the automotive field. The purpose of this study was to test the development of Smart Apps Creator (SAC) to create interactive learning resources for Engine Management Systems (EMS). This research and development (RD) project used the ADDIE development approach. Five subject matter experts and five media specialists comprised an expert assessment group that validated and evaluated the media to ensure its feasibility. In addition, 62 students reviewed the learning materials as users of the application. The media specialists' evaluation of the feasibility of the learning media construction resulted in a score of 4.02, which is considered practical. The subject matter experts' evaluation of the feasibility of the learning media material resulted in a score of 4.15, which is considered practical. The students' evaluation of the acceptance of the learning media as users resulted in a score of 4.07, which is classified as practical. Meanwhile, the application implementation in the learning process proved to increase learning success among students who used the program development. All things considered, the findings of this study can be used as evidence that application-based learning materials are worthy of widespread use, which will further improve teaching standards. Furthermore, vocational teachers must innovate in developing learning media by utilizing and integrating technology into the process. The creation of such media is necessary in the 21st century to provide easily accessible and understandable learning materials so that students can effectively absorb the information.
A Systematic Literature Review of Technopreneur Ship Fashion Design Purnama, Rahayu; Prabawati, Melly; Radiona, Vivi; Sesnawati, Yeni; Tajuddin, Rosita Mohd; Noor, Muhamad Aiman Afiq Mohd
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1526

Abstract

The fashion industry requires Technopreneur fashion design to face the challenges of the technology and digitalization era in preparation for the 5.0 industrial age. Entrepreneurship dimensions, namely autonomy, innovativeness, risk-taking, proactive, and technology proficiency, are confident insufficient for Technopreneur ship due to their limited resources and lack of knowledge and access to foreign Technopreneur ship in fashion design. This study identifies and reviews the literature on Technopreneur ship orientation fashion education in Scopus between 2010 and 2025. This study identifies and reviews literature on technopreneurs’ orientation from scientific domains: entrepreneurial dimensions and entrepreneur-based technology drivers in fashion design. A systematic approach was adopted, recognizing 25 relevant articles from published journals indexed by Scopus collected from 2010 to 2025. The lack of literature on the technopreneur dimension has resulted in 10 dominant and representative articles originating from Scopus indexed journals and other related journals indexed by Google Scholar collected from 2002-2025. This study consists of two essential parts: 1) descriptive analysis, discussing the characteristics of the related articles, the country of the study, and the methods used. 2) thematic analysis, discussing the six essential categories of drivers in the adoption of technopreneurship and more deeply. The results regarding creating future ideas mean the same as autonomy, business innovation is innovation in the entrepreneurial dimension, seeking opportunities means being proactive, creating new businesses means the same as risk-taking, and technological proficiency are common expressions from several literatures regarding views on technopreneurship itself that do not originate from the entrepreneurial orientation that exists in the previous literature. This study proposes a conceptual framework of technopreneur orientation in fashion design education to develop a sustainable fashion design curriculum in the future.
Cross Modal-FT Net: A Multimodal Fake News Detection Framework using Text, Images, and User Behavior Karnan, K; Aravind Babu, L.R
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1245

Abstract

An unprecedented proliferation of fake news across digital platforms is a major hurdle for reliable information, people trust, and social stability. Current fake news detection techniques, primarily based on text analysis, frequently overlook the multimodal and behavioral indicators associated with contemporary misinformation. Multimodal approaches are rarer and typically classify news as either genuine or fraudulent. To address this problem, this paper proposes a CrossModal-FTNet (Fake News Transformer Network), a transformer-centric multimodal system that identifies fake news by analyzing text, associated images, and user actions such as likes, shares, and the reliability of sources. The suggested model includes three dedicated encoders: a BERT-inspired text encoder for contextual interpretation, a ResNet-50-inspired image encoder for visual cues, and a lightweight behavioral feature encoder for examining user interaction information. These varied representations are subsequently merged through a cross-modal fusion transformer, which synchronizes and enhances data from various sources into a single united feature space. Experiments on benchmark datasets such as Fakeddit, Weibo, MM-COVID, and Twitter15 indicate that the suggested model excels, attaining 94.3% accuracy and a 92.8% F1-score, outpacing multiple unimodal and early fusion baselines. The findings confirm that using cross-modal data greatly boosts the ability to detect fake news. Thus, CrossModal-FTNet offers a scalable, real-time, and precise solution for combating misinformation in the ever-changing online environment.
Hybrid CNN-LSTM Model for Predictive Maintenance of Wind Turbine Systems Jiang, Qi
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1679

Abstract

Predictive maintenance enhances the reliability and efficiency of wind turbine systems through its role in managing these wind energy systems, which represent the most commonly used renewable resource worldwide. This research develops a combined Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) framework to refine fault detection as well as maintenance tactics using Supervisory Control and Data Acquisition (SCADA) measurements. Through its spatial pattern extraction ability, CNN operates on multivariate sensor data, while LSTM maintains temporal dependencies to recognise complex time-dependent degradation patterns. The proposed Hybrid CNN-LSTM model achieved outstanding predictive maintenance performance for wind turbines with an accuracy of 96.5%, precision of 96%, and recall of 95.5%. It outperformed CNN (accuracy: 91%), LSTM (89.5%), and Random Forest (83.5%) in all key metrics. The model also achieved the highest F1-score (96%) and AUC (0.96), proving its reliability in real-time fault detection. Verification of the methodology involves testing it on real SCADA data from two wind farm sites over two years, where it proves capable of spotting abnormal operations at early stages. Secure wind energy operations, along with efficient cost reduction, become feasible through the use of this solution, which reduces unexpected equipment failures while minimising downtime events.
An Effective Approach for Musical Theatre Curriculum in Pedagogical Innovation Li, Jialin; Kim, Hyuntai
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1083

Abstract

Musical theatre education necessitates a flexible and well-structured curriculum that combines creative instruction, theoretical knowledge, and current pedagogical practices. However, many existing curricula continue to face challenges, such as limited resource allocation, a lack of adaptive learning strategies, and insufficient opportunities for personalized learning paths. These gaps often lead to poor student performance, low engagement, and unsatisfactory feedback from instructors. To address these issues, this study introduces the Musical Theatre Curriculum Planning Algorithm (MTCPA). This curriculum optimization framework combines adaptive learning with a project-based approach, leveraging traditional, digital, and experiential learning sources. The MTCPA was evaluated using a dataset of 200 students that incorporated blended learning methods, gamification elements, and AI-assisted feedback mechanisms. The instructional materials were divided into three main categories: acting, singing, and dancing. The framework's effectiveness was measured using key indicators, including student performance outcomes, engagement levels, and instructor evaluations. The results show significant improvements: student performance scores increased by 27%, engagement levels increased by 35%, resource utilization increased by 40%, and teacher satisfaction with the curriculum design increased by 30%. The proposed algorithm not only improves classroom performance but also enhances long-term skill retention through practical application, promoting early career readiness in the competitive fields of musical theatre and the performing arts. Furthermore, the data-driven, adaptive nature of MTCPA enables a structured yet innovative approach to curriculum planning, leading to more effective decision-making and pedagogical creativity. To summarize, the MTCPA represents a significant step forward in musical theatre education, demonstrating how incorporating adaptive, personalized, and technology-supported learning can result in measurable improvements in student success, engagement, and curriculum efficiency. By combining traditional methods with modern innovations, MTCPA helps to reshape musical theatre pedagogy, ensuring that students are better prepared to face both academic and professional challenges in the performing arts.
Influence of Online Transportation on Mandatory and Maintenance Activities in Banda Aceh Novriza, Ferdiansyah; Agusmaniza, Roni; Firnanda, Ary; Zarita, Santi Septiana; Yusra, Cut Liliiza
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1482

Abstract

Online transportation has experienced significant growth and has become a vital element in the daily activities in Banda Aceh. Services such as Maxim, Grab, Kururio, Mr. Delivery, Sidoom, and Umma offer convenient access to transportation, goods delivery, and food services, illustrating the growing integration of digital technology into daily urban mobility and lifestyle patterns. In the context of fast-paced urban life, these platforms significantly influence the mobility patterns of the community, both in mandatory activities (such as working and studying) and maintenance activities (such as shopping, picking up children from school, and others). This study highlights the significance of examining how online transportation influences community life. It aims to assess its social, economic, and environmental impacts, identify key determinants of user preferences, and evaluate its overall contribution to improving quality of life within the evolving dynamics of urban mobility. This study employed a mixed-methods approach by integrating quantitative and qualitative techniques, with surveys serving as the primary instrument for data collection. The results indicate that the use of online transportation is influenced by factors such as income, travel time, age, gender, and household size. In terms of service preferences, Food and goods delivery dominates usage (42.9%), followed by motorcycle ride-hailing (38.1%) and cars (19%). These findings underscore the increasing significance of online transportation services in meeting daily needs and enhancing urban mobility, particularly in the areas of goods and food delivery. The results also indicate that public perceptions of the environmental impacts of online transportation remain balanced. While respondents value the improved accessibility and convenience offered by online transit, they are aware of its negative externalities, particularly its role in exacerbating traffic congestion and air pollution.
Integration of Artificial Intelligence in Academic Research: To What Extent Do Students' Knowledge, Understanding, and Use Depend on Technology? Iriani, Tuti; Azisah, Nur; Luthfiana, Yusrina; Nugroho, Bimo
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1515

Abstract

The development of artificial intelligence (AI) technology has had a significant impact on higher education. This study aims to assess the level of knowledge, understanding, and use of AI among students in the context of final project preparation. This study uses a quantitative descriptive approach to measure three main dimensions—knowledge, understanding, and practical use (application) in the context of academic research. The population in this study consisted of 172 students from the Faculty of Engineering, Universitas Negeri Jakarta, who were conducting academic research. The sampling technique employed was non-probability sampling, utilizing a purposive sampling approach. Data analysis used exploratory factor analysis (EFA). The results showed that students have excellent knowledge of AI. Meanwhile, the understanding of AI shows varying levels, with the majority falling into the sufficient and low categories, indicating a need to improve AI literacy. The use of AI by students is primarily focused on aspects of writing, research, and document creation, with a reasonably consistent usage pattern and an average duration of 1-2 hours per session. These findings confirm that students actively utilize various AI in the academic process, but still require training and supervision to ensure that AI use can be carried out ethically and responsibly. The results of this study are important as a basis for developing institutional policies and ethical regulations related to the integration of AI into academic processes, as well as a reference for designing effective training programs to improve students' competency in optimally utilizing AI technology.
Predicting Burnout in Start-Up Environments: A Multivariate Risk Scoring Approach for Early Managerial Intervention Sutrisno, Nos; Elveny, Maricha; Lubis, Andre Hasudungan; Syah, Rahmad; Hartono, Hartono; Krisdayanti, Sabina
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1663

Abstract

Start-up organisations operate under fast timelines, lean staffing, and constantly shifting priorities, exposing employees to chronic workload pressure and emotional strain. Unmanaged burnout in these settings threatens individual well-being, talent retention, and long-term execution capacity. This study proposes a multivariate burnout risk scoring approach that aims to identify and prioritise employees at elevated risk before full deterioration occurs, enabling early managerial intervention rather than reactive recovery. The proposed pipeline integrates principal component analysis (PCA), Random Forest, and Support Vector Machine (SVM). PCA is first applied to reduce redundancy across workplace indicators, yielding five principal components (PC1–PC5) that together explain 88% of the total variance in self-reported stress level, job satisfaction, emotional exhaustion, work-life balance, performance, and social interaction. These components are then used as predictors in two supervised classification models, Random Forest and SVM, to estimate the likelihood that each employee belongs to a high-burnout-risk class. The Random Forest model achieved an accuracy of 88%, and the SVM model achieved an accuracy of 86%, demonstrating strong predictive capability in distinguishing higher-risk employees from lower-risk employees. The resulting predicted probability is interpreted as an individualised burnout risk score, which can be mapped to action categories such as workload redistribution, role clarification, targeted supervisory check-ins, or temporary protection from critical-path tasks. In this way, the framework operationalises burnout prediction not only as a detection task but also as an actionable decision-support signal for leaders. The study therefore offers both a quantitative method for forecasting burnout in start-up environments and a practical structure for translating prediction into preventive intervention.
Determinant Factors Influencing Entrepreneurial Interest among Vocational School Students in Electronics Engineering Hartati, Hartati; Supriyadi, Edy; Setiawan, Dedi; Hamid, Mustofa Abi; Nurtanto, Muhammad; Hakiki, Muhammad
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1504

Abstract

This research investigates the various factors that affect entrepreneurial interest among vocational secondary school students enrolled in the electronics engineering program in Yogyakarta, Indonesia. The study identifies entrepreneurship as a crucial mechanism for fostering innovation, self-employment, and enhancing national competitiveness. It examines five primary determinants: self-efficacy, family support, entrepreneurial attitude, entrepreneurship education, and social and institutional support. A quantitative ex post facto methodology was utilized, involving 104 respondents chosen through proportional random sampling from three vocational institutions.  Data collection employed a validated four-point Likert scale questionnaire, with analysis conducted via simple and multiple linear regression techniques utilizing SPSS. The findings indicate that all five variables have significant and positive impacts on students' entrepreneurial interest, both independently and in combination. Entrepreneurship education and social–institutional support exhibit the most significant impact, underscoring the critical role of practical learning, mentorship, and supportive ecosystems in shaping entrepreneurial trajectories.  Self-efficacy and family support enhance motivation and confidence, while positive entrepreneurial attitudes promote perseverance and proactive engagement in opportunity recognition. These factors account for nearly half of the variance in entrepreneurial interest, thereby affirming the significance of the Theory of Planned Behavior and Social Cognitive Theory within vocational contexts. This study empirically enhances the discourse on entrepreneurship in technical and vocational education by highlighting the combined influence of psychological, familial, educational, and structural supports on the development of entrepreneurial intentions. Policy implications indicate that promoting entrepreneurship necessitates the alignment of curricular design, family involvement, and institutional policies to enhance entrepreneurial ecosystems within vocational education. Vocational schools can enhance student empowerment by fostering self-efficacy and offering accessible institutional resources, enabling the translation of entrepreneurial aspirations into sustainable ventures.

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