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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
Core Subject : Science, Education, Social, Engineering,
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation
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 582 Documents
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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.
Propagation Faults in Real-Time Content Streaming Across Low-Bandwidth Learning Infrastructure Sappa, Ankita
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1447

Abstract

Delivering live educational videos in places with thin internet pipes is still tough because the signal breaks often, showing up as lost frames, endless rebuffering, or delays that pile on top of one another. In response, this paper builds a detailed simulation tool that tests how these failures unfold across different hardware layouts and network grades, paying special attention to bandwidth, mixed devices, and cache-based buffers. The experiments find that storing key content at the edge cuts the average stalls by more than 40 per cent versus relying on a distant central server, a gap that widens under the 512-kbps cap. A three-dimensional model of delay spread further shows that both pause rates and picture quality drop rise sharply, not linearly, as bandwidth jitter and the number of viewers climb. The work also pinpoints fault link patterns tied to specific protocols and suggests tuning buffer sizes along with smarter retry timings to dampen these cascades. Taken together, the results give clear design tips for rolling out remote learning where infrastructure is weak.
Re-Analysis of the Prototype Structure of Earthquake-Resistant Flats Built in the Seismic Mitigation Area Central of Borneo Su, Johan; Kraugusteeliana, Kraugusteeliana; Irwansyah, Defi
International Journal of Engineering, Science and Information Technology Vol 3, No 4 (2023)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v3i4.472

Abstract

Indonesia is an earthquake-prone area; to reduce the risk of disasters, it is necessary to construct earthquake-resistant buildings. The concept of earthquake-resistant buildings attempts to make all structural elements into a unified whole that is not easily collapsed by an earthquake. In general, the planning of the structure of an apartment is made of a prototype whose structure is calculated to be earthquake-resistant. However, not all flats are built in earthquake-prone areas. One is in Central Borneo Province, which is not prone to earthquakes. The research aims to determine the comparison of the dimensions and reinforcement requirements on the prototype with Kriteria  Desain  Struktur (KDS) 'BC' Structural Design Criteria compared to structural planning in the Central Borneo Seismic Mitigation Area. Design standards refer to SNI 1727:2013, SNI 2847:2013, SNI 2847-2019, and SNI 1726-2019. The building being studied is the Type 36 Prototype Flat (5 floors) using concrete fc' 22.8 MPa and reinforcing steel my 420 MPa. Research on Columns and Beams' superstructure includes the design of the structural dimensions and reinforcement requirements. Structural dimensions and reinforcement area will be designed efficiently and declared safe by controlling the reinforcement ratio(p). Structural dimensional limitations. Structural calculation analysis using the  ETABS computer application.
Analysis of The Interrelationship of Human Resource Performance, Digital Service Quality, Perceived of Service Value and Customer Loyalty Karyono, Karyono; Violin, Vivid; Osman, Isnawati; Gusti Rao, Don; Apramilda, Riesna
International Journal of Engineering, Science and Information Technology Vol 4, No 3 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i3.527

Abstract

The purpose of this study is to evaluate the comparison of customer loyalty levels between conventional travel agents and travel agents that use digital strategies in their business processes. This study uses a descriptive and quantitative approach. Data collection methods use surveys and snowball sampling techniques. The results of the study indicate that there is a significant difference in the level of customer loyalty between conventional and online travel agents. Conventional travel agent consumers tend to be more loyal because they receive direct interaction with travel agency managers, customers also get direct service from staff, this direct service and interaction have been shown to increase customer satisfaction and loyalty. Online travel agent consumers are more price sensitive and have lower loyalty levels, even though they choose to use digital services considering effectiveness and efficiency factors. The conclusion of the study is that conventional travel agency consumers prefer personalized services and direct interaction with service providers, while online travel agency consumers prioritize price and have considerations for access to reviews in determining travel agents. Researchers suggest that management design an effective strategy to combine conventional and digital activities in the business process and services provided to customers, conventional travel agents must continue to emphasize direct interactions that have been well established and excellent, while online agents must improve customization elements and customer service to increase loyalty.
AI-driven Quantum Dot Transistors for Ultra-Low Power Computing Mishra, Archana; Kadao, Anjali Krushna; Rohilla, Shruti
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1350

Abstract

Since Quantum Dot Transistors (QDTs) provide a transformative approach to ultra-low power computing, yet their optimization is an open problem, a proposed paradigm shift in computing is used as an example application context for creating new processors. The framework of this research is an AI-based approach to dynamically improve the QDT's efficiency and flexibility using reinforcement learning and neuromorphic AI. The intelligent tuning mechanism proposed uses a sample-as-a-service approach to optimize charge transport and lower leakage currents, as well as minimize energy dissipation according to real-time workload. To precisely control and self-adjust from transistor behavior to a varying environmental condition, it integrates a hybrid quantum-classical AI model. Furthermore, the mechanism adopts self-healing features to autonomously reconfigure transistor networks when anomalies are encountered, ensuring fault tolerance and extending device longevity. Simulations are used to validate the proposed methodology, which is shown to improve power efficiency, switching speed, and operational stability a great deal versus conventional low-power transistors. This work takes most of the power of QDTs for next-generation energy-efficient electronics such as IoE, edge computing, and neuromorphic processors by leveraging AI-driven optimization. Their findings provide significant contributions in the emerging field of AI-assisted semiconductor technology toward developing a scalable and intelligent method for designing ultra-low power devices. Future advancements in sustainable computing lie in the performance improvements while decreasing the digital system’s environmental footprint that this research enables.
Utilization of Machine Learning for Stunting Prediction: Case Study and Implications for Pre-Matrical and Pre-Conceptive Midwifery Services Aini, Qurotul; Rahardja, Untung; Sutedja, Indrajani; Spits Warnar, Harco Leslie Hendric; Septiani, Nanda
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1488

Abstract

Stunting, a global health challenge, affects millions of children, particularly in low- and middle-income countries, and has lasting consequences on cognitive development, physical growth, and overall well-being. Early prediction and intervention are crucial for reducing stunting, especially before conception and during early pregnancy. This paper explores the utilisation of machine learning (ML) for predicting stunting risk in the context of pre-maternal and pre-conceptive midwifery services. By analysing a case study, the research assesses the effectiveness of various machine learning algorithms in identifying stunting risk factors, including maternal health, nutrition, socioeconomic status, and environmental conditions. Using healthcare and demographic data, the study develops predictive models to assist midwives in assessing stunting risks during pre-conception and prenatal phases. The findings demonstrate that ML models, particularly random forest and support vector machine algorithms, outperform traditional risk assessment methods, providing higher accuracy and earlier detection of stunting risk. These models enable midwives to deliver personalised care and targeted interventions, optimising maternal and child health outcomes. The study also highlights the broader implications of integrating machine learning into midwifery services, including improved decision-making, resource allocation, and healthcare efficiency. In conclusion, this research underscores the transformative potential of machine learning in predicting stunting risk and enhancing the effectiveness of pre-maternal and pre-conceptive midwifery services, offering a promising approach to mitigating the global burden of stunting.

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