cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Dahlan Abdullah
Contact Email
dahlan@unimal.ac.id
Phone
+62811672332
Journal Mail Official
ijestyjournal@gmail.com
Editorial Address
Jl. Tgk. Chik Ditiro, Lancang Garam, Lhokseumawe, Aceh - Indonesia, 24351
Location
Kota lhokseumawe,
Aceh
INDONESIA
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 80 Documents
 1   2   3   4   5 
Search results for , issue "Vol 5, No 3 (2025)" : 80 Documents clear
Data-Driven Decision-Making Use Case: Applying Big Data Analytics to Forecast Important Decisions Prasath, A Rama; Leelavathy, S; Aruna Sri, P S G; Saranya, G; Manikanthan, S V
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.1122

Abstract

Due to decreased material and resource usage and other tooling needs, additive manufacturing (AM) has rapidly developed over the past 10 years. It has shown significant promise for energy-efficient and environmentally friendly production. As manufacturing technologies have advanced in the modern period, intelligent manufacturing has gained greater attention from academia and business to increase the sustainability and efficiency of their output. Few studies have examined the effects of big data analytics (BDA) in CSR activities on CSR performance, despite the growing number of businesses implementing BDA in CSR initiatives. As digital technology is incorporated into various processes, supply chain management is increasingly interested in Big Data Analytics (BDA). It efficiently makes the transfer of goods and information possible. Nevertheless, little research has been done on how much BDA can enhance supply chains' environmental sustainability, even though it offers several benefits. We provide a thorough understanding of "data science" in this paper, covering a range of sophisticated analytics techniques that may improve an application's intelligence and capabilities through astute decision-making in diverse contexts. In light of this, we conclude by outlining the difficulties and possible lines of inquiry within the parameters of our investigation. Our literature analysis indicates that an increasing number of data-driven decision-making methods have been developed specifically to benefit from the wealth of sensor-generated data in the context of Industry 4.0. This article aims to provide researchers, decision-makers, and application developers with a reference point on data science and advanced analytics, especially regarding data-driven solutions for real-world issues.
Documentary Video Introduction of Modern Tebe System Based on Video in Cemenggaon Village, Sukawati, Gianyar Palguna Brahmanta, I Wayan Agus; Surya Dinata, Ramanda Dimas; Pradnyanita, Anak Agung Sagung Intan
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.890

Abstract

Cemenggaon traditional village, located in Sukawati Gianyar subdistrict, has developed a modern tebe system to deal with the problem of organic waste. This modern tebe has been implemented in every resident's house, with around 245 heads of families already having at least two modern tebe. Cooperation between the government, stakeholders, and others is needed to manage non-organic waste. Also, residents, where several waste banks and non-organic waste have been prepared, will be sorted and have a sale value. Introducing the modern tebe system to the broader community, especially the younger generation, will train a responsible attitude towards preserving nature by caring for and keeping the environment clean of rubbish. Some respondents do not know and do not have sufficient insight into organic waste management, nor do they know how to handle organic waste using the modern tebe system.
Hybrid Deep Fixed K-Means (HDF-KMeans) Zuhanda, Muhammad Khahfi; Kohsasih, Kelvin Leonardi; Octaviandy, Pieter; Hartono, Hartono; Kurnia, Dian; Tarigan, Nurliana; Ginting, Manan; Hutagalung, Manahan
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.913

Abstract

K-Means is one of the most widely used clustering algorithms due to its simplicity, scalability, and computational efficiency. However, its practical application is often hindered by several well-known limitations, such as high sensitivity to initial centroid selection, inconsistency across different runs, and suboptimal performance when dealing with high-dimensional or non-linearly separable data. This study introduces a hybrid clustering algorithm named Hybrid Deep Fixed K-Means (HDF-KMeans) to address these issues. This approach combines the advantages of two state-of-the-art techniques: Deep K-Means++ and Fixed Centered K-Means. Deep K-Means++ leverages deep learning-based feature extraction to transform raw data into more meaningful representations while employing advanced centroid initialization to enhance clustering accuracy and adaptability to complex data structures. Complementarily, Centered K-Means improve the stability of clustering results by locking certain centroids based on domain knowledge or adaptive strategies, effectively reducing variability and convergence inconsistency. Integrating these two methods results in a robust hybrid model that delivers improved accuracy and consistency in clustering performance. The proposed HDF-KMeans algorithm is evaluated using five benchmark medical datasets: Breast Cancer, COVID-19, Diabetes, Heart Disease, and Thyroid. Performance is assessed using standard classification metrics: Accuracy, Precision, Recall, and F1-Score. The results show that HDF-KMeans outperforms traditional K-Means, K-Means++, and K-Means-SMOTE algorithms across all datasets, excelling in overall accuracy and F1 Score. While some trade-offs are observed in specific precision or recall metrics, the model maintains a solid balance, demonstrating reliability. This study highlights HDF-KMeans as a promising and effective solution for complex clustering tasks, particularly in high-stakes domains like healthcare and biomedical analysis.
Public Facility Recommendation System in Subulussalam City Using Fuzzy C-Means Algorithm Berutu, Indah Fachlira; Dinata, Rozzi Kesuma; Afrillia, Yesy
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.873

Abstract

Subulussalam City, as one of the autonomous regions in Aceh Province, Indonesia, has excellent potential to develop public facilities to improve the quality of life for its residents. Recommendation systems have become an effective solution in helping users find relevant information based on the preferences and needs of the community. This research focuses on developing a recommendation system using the Fuzzy C-Means algorithm. This algorithm is one of the clustering methods capable of handling uncertainty and ambiguity in data. This study aims to develop and analyze a public facility recommendation system in Subulussalam City using the Fuzzy C-Means algorithm. The dataset in this study was obtained from the Youth, Sports, and Tourism Office of Subulussalam City and the results of a research questionnaire. Regarding the names of each public facility, it provides information about the location and various forms of visitor assessments, including evaluations related to accessibility, facilities, costs, environment, and visitor experiences, using a rating scale of 1-5. Based on the testing results, the Fuzzy C-Means clustering algorithm can group facilities based on characteristics and user preferences, resulting in more personalized and relevant recommendations. The data to be clustered is divided into two categories: recommended and not recommended. The study's results using the Fuzzy C-Means algorithm show the final grouping based on the degree of membership from the last iteration of each public facility, with cluster 1 containing 31 locations and cluster 2 containing 31 locations.
Study on Magnetic Properties Characterization of Aceh Iron Sand as Raw Biomedical Application Materials Sayuti, Muhammad; Yusuf, Muhammad; Putra, Reza; Wirawan, Riza
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.975

Abstract

The magnetic properties characterization of Aceh iron sand as the preferred material for biomedical applications was studied. Meanwhile, Aceh's iron sand is used as raw cement-making material. It is hoped that in the future, it can be used in many different biological and medical applications, such as diagnostic tests for early disease detection, to serve as tools for non-invasive imaging and drug development. Samples of the natural resource were prepared using a magnetic separator, and the concentrates were mashed by the ball milling method to achieve 112.7µm (MK), 119.3 µm (MT), 112,4 µm (LP), and 115.1 µm (SK) particle size. These features were evaluated from loop hysteresis using a vibration sample magnetometer (VSM), while x-ray diffraction (XRD) was employed to analyze iron oxide. The results estimated the values of saturation magnetization, remanent magnetization, and coercivity from Mon Klayu, Mantak Tari, Lam Panah, and Syiah Kuala at 67.79 emu/g, 10.36 emu/g and 0.02 T; 83.49 emu/g, 13.22 emu/g and 0.02 T; 62.17 emu/g, 9.32 emu/g and 0.02 T; 73.26 emu/g, 10.34 emu/g and 0.02 T, respectively. However, Fe3O4 (magnetite) occurred predominantly in the selected locations.
Analysis of Forehand and Backhand Stroke Accuracy and Lateral Epicondylitis Pain among Recreational Tennis Players Mathew A, Ashish; Farzana, S F Mariyam; T N, Suresh; M, Arvind; V, Prithiha
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.1134

Abstract

The tennis matches require short explosive bursts of energy per match or practice session, and an average tennis match lasts less than one hour or as long as five hours. Tennis players most prominently use the primary ground strokes, such as forehand and backhand strokes. The forehand and backhand strokes are simultaneously activated by a complex sequence of muscle activity that incorporates smooth trunk and lower extremities coordination patterns. Accuracy of the forehand and backhand stroke plays a dominant role in the tennis matches, because accurate movement leads to high-performance skills. The contraption of this study promotes the knowledge on the influence of lateral elbow pain, which affects the players' accuracy in performing the ground strokes during a match, significantly decreasing the players' performance. The participants were recruited according to the inclusion and exclusion criteria. The participants' lateral epicondylitis was assessed using the Cozens test, pain was evaluated using the Numeric pain rating scale, and the ground stroke accuracy was assessed using the Wiebe tennis performance test. During the forehand stroke, the participants reported a visual analogue scale with a mean value of 2.46 and an accuracy rate of 65.71. During the backhand stroke, the participants reported a visual analogue scale with a mean value of 5.66 and an accuracy rate of 37.93. This study concludes that the pain score significantly increased in double and single backhanded strokes, with a decreased accuracy rate. This study also concludes that at least a positive correlation exists between pain intensity and the accuracy rate in the backhand stroke.
Tensile and Flexural Properties of Epoxy Nanocomposites Reinforced with Cellulose Nanocrystals Azhary, Taufik; Pajri, Afril Efan
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.892

Abstract

Composite materials are extensively utilized across various fields such as engineering, aviation, automotive, construction, and healthcare. This widespread application highlights their superior properties, often absent in the individual constituent materials. Additionally, composites offer the advantage of being easily fabricated to meet specific requirements, and incorporating natural fibers as reinforcement has gained significant interest due to their environmental friendliness and abundance. Among these, nanocellulose is a promising green material due to its unique characteristics. Specifically, cellulose nanocrystals (CNC), nanoscale derivatives of nanocellulose, have attracted considerable attention as reinforcement agents in composite fabrication. This interest stems from CNC's notable advantages, including excellent mechanical properties, a high crystallinity index, plentiful availability, low weight, and eco-friendly nature. This study was undertaken to investigate the impact of varying concentrations of cellulose nanocrystal (CNC) (0, 0.5, 0.75, 1 wt%) on the mechanical properties, specifically the tensile and flexural properties, of epoxy resin/cellulose nanocrystal (E/CNC) nanocomposites. The materials employed in this research include epoxy resin, hardener, and cellulose nanocrystals. The fabrication of the E/CNC nanocomposites was carried out through a straightforward mixing method, wherein the constituent materials were blended following the defined experimental parameters, followed by the molding process. The findings of this study indicate that the incorporation of cellulose nanocrystals (CNC) significantly enhances the mechanical properties of E/CNC nanocomposites. The E/0.75CNC nanocomposite showed optimal tensile strength (39.91 MPa; +4.95%), while E/1CNC exhibited superior flexural strength (65.78 MPa; +5.08%) compared to the unmodified epoxy baseline.
Learning Sanskrit to Strengthen Multiculturalism and Religious Moderacy Surada, I Made; Subagia, I Nyoman; Sura Adnyana, Putu Eka
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.968

Abstract

This paper discusses Sanskrit language learning as a strategic instrument in strengthening the values of multiculturalism and religious moderation in Indonesia. Sanskrit has not only historical value as a heritage of Hindu-Buddhist civilization but also contains universal teachings such as dharma, Ahimsa, tat twam asi, and vasudhaiva kutumbakam, which are relevant in the context of a plural society. Through a qualitative approach with observation, Documentation, and literature study methods, this research shows that Sanskrit learning can shape the character of students who are tolerant, inclusive, and have a nationalistic outlook. The learning model developed is contextual, dialogical, and collaborative and integrates the values of diversity and interfaith understanding. Despite facing challenges such as the stigma of exclusivism, limited teachers, and low motivation to learn, learning Sanskrit remains relevant for character education and strengthening social cohesion. Therefore, innovative pedagogical strategies and inclusive curriculum policies are needed so that Sanskrit can contribute significantly to building a harmonious Indonesian society with diversity.
Composite Material Engineering Analysis Based on Circular Economy for the Conservation of Interior Ornaments and Traditional Balinese Architecture Jaya, I Kadek Prana; Dewi, Ni Made Emmi Nutrisia
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.919

Abstract

This study examines the engineering and application of sustainable composite materials as an alternative to traditional Balinese architectural ornaments through a comparative analysis of four material types: fiberglass, precast concrete, glass fiber-reinforced cement (GRC), and artificial sandstone. The scarcity of natural materials, growing ecological pressures, and the demand for economic efficiency and ease of production have driven the exploration of engineered materials that can represent Balinese architecture's aesthetic, symbolic, and spiritual values. The research employs a descriptive-qualitative methodology involving field observations, in-depth interviews with local artisans, and an analysis of each material's technical and cultural characteristics. Fiberglass and GRC stand out for their form flexibility and suitability for mass production, while precast concrete offers superior structural durability and long-term maintenance efficiency. Meanwhile, community-driven innovations in artificial sandstone exhibit strong potential for preserving traditional values while addressing contemporary sustainability challenges. The findings suggest that no single material emerges as universally superior; therefore, material selection should be context-dependent, considering both economic feasibility and cultural compatibility. The study concludes that integrating material innovation into traditional architecture must be grounded in circular economy principles, active community participation, and a deep understanding of vernacular values. These insights are expected to serve as a strategic reference for material selection in preserving Balinese cultural heritage while supporting the contextual and competitive development of the local creative industry within the Southeast Asian region.
Implementation of the Simple Additive Weighting Algorithm for Café Recommendations in Lhokseumawe City Arkan, Raihan; Safwandi, Safwandi; Ar Razi, Ar Razi
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.885

Abstract

The selection of cafés that match customer preferences is a challenge, especially in the city of Lhokseumawe, which has 30 cafés with different characteristics. This research implements the Simple Additive Weighting (SAW) algorithm to provide recommendations for the best café based on six criteria, namely price (weight 0.25), menu (0.2), order duration (0.15), service (0.2), facilities (0.15), and discounts promotions (0.05). The recommendation system was developed using a combination of Laravel PHP and Python, where Laravel is used to build an interactive web interface. Python also plays a role in data processing and complex mathematical calculations. The results showed that the system was able to provide optimal recommendations, with Petrodollar Coffeeatery Roastery as the top choice based on the calculation of the highest preference values (3.28 for price, 2.48 for menu, 3.16 for order duration, 2.88 for service, 2.96 for facilities, and 2.8 for discounts promotions). TR Coffee and Platinum Coffee occupy the following positions. In addition, this study found that the weight of the criteria and the number of datasets (150 reviewers) significantly influence the quality of recommendations. The more representative the weights used and the larger the dataset analyzed, the more accurate the system will produce recommendations based on user preferences. Thus, weight optimization and dataset expansion are essential factors in improving the effectiveness of SAW-based recommendation systems.

Page 1 of 8 | Total Record : 80

 1   2   3   4   5 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol 5, No 4 (2025) Vol 5, No 3 (2025) Vol 5, No 2 (2025) Vol 5, No 1 (2025) Vol 4, No 4 (2024) Vol 4, No 3 (2024) Vol 4, No 2 (2024) Vol 4, No 1 (2024) Vol 3, No 4 (2023) Vol 3, No 3 (2023) Vol 3, No 2 (2023) Vol 3, No 1 (2023) Vol 2, No 4 (2022) Vol 2, No 3 (2022) Vol 2, No 2 (2022) Vol 2, No 1 (2022) Vol 1, No 4 (2021) Vol 1, No 3 (2021) Vol 1, No 2 (2021) Vol 1, No 1 (2021) More Issue