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Dahlan Abdullah
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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 593 Documents
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Application Dictionary of Scientific Plants and Animals Android-Based Algorithm Using Jaro Winkler Distance Rasna, Rasna; Rosiana Dewi, Ni Wayan Emmy; Bani, Alexius Ulan; Lamsir, Seno; Nugroho, Fifto
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.839

Abstract

The dictionary is a kind of reference book composed of abjad and contains terms of terms and their meanings. Dictionaries are needed in education to figure out the word or term you want to know its meaning. In education, it is found in many terms, for example, in the biological sciences. In biology, there is the term a scientific term that must be known to every student, especially those who pursue the field of biology. The scientific term, or scientific name, is the Latin name of plants and animals and is one of the critical discussions in the biology field contained in the course curriculum of elementary school, junior high school, and senior high school lectures. The field of biology is the subject of the taxonomy of plants and animals, and each student is required to know the Latin of every plant and animal. This is because plants and animals in the world of biology are known to scientists with scientific language. In this research, the author applies the scientific language dictionary of plants and animals using an algorithm based on the android Jaro Winkler distance. Jaro Winkler's distance algorithm searches for the desired plants and animals. In this study, the plant names and scientific names are taken from existing books and journals. Each name consists of 1000 names of plants and animals, with each of the 500 names of plants and 500 animal names along with scientific language and the images, respectively. The system will generate output from the scientific names of plants and animals and be equipped with pictures and explanations. The results from this study use an algorithm called Jaro Winkler Distance to search for the names of the desired plants and animals by matching each character entered with the characters in the database.
Implementation of the First Come First Served Method in a Website-Based Sports Facility Reservation Service System Rangkuti, Irsan Efendi; Taufiq, Taufiq; Suwanda, Rizki
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.859

Abstract

The people of Kotanopan have a high interest in sports such as futsal and badminton, an interesting phenomenon that shows the popularity of these sports and opens up many business opportunities. Most sports facilities for rent still use a conventional system where prospective renters must come directly to the field or call the manager to make a reservation, making it prone to errors in the reservation process. From the management's side, they often encounter obstacles when processing tenant reservations, especially when sorting the schedules that the tenants have created. This research aims to build a sports facility reservation service system using the First Come, First Served (FCFS) method. This method is the most suitable scheduling system for the sports facility reservation system in Kotanopan. The results of the First Come First Served (FCFS) method experiment with a random trial of 5 users, each with execution times of 3, 3, 5, 5, and 9, yielded an average waiting time of 1 minute and an average reservation completion time of 6. With the test results showing that the system can meet the needs and has functions accessible to every system user, it is hoped that this system can facilitate users in making reservations online.
Mapping Customer Engagement Research: A Bibliometric Analysis Tanjung, Lutfiyanah; Damayanti, Dhea Ajeng; Setiawan, Adi
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.860

Abstract

This study aims to map research development on customer engagement (CE) comprehensively. This qualitative research conducts historical and bibliometric analysis of quality-standard scholarly articles published in leading international journals. CE has experienced significant growth in the last decade, especially in 2021. Bibliometric analysis was used to analyze articles from Elsevier, Emerald, Springer, Taylor Francis, and IEE databases. A search using Publish or Perish from 2007 to 2025 resulted in 621 articles. Co-occurrence analysis found 1,352 keywords derived from titles and abstracts. The occurrence of keywords is limited to 5; from the limitation of the occurrence, 69 keywords are divided into 8 clusters. Through visualization of research trends and author collaboration networks, bibliometric analysis is essential for developing CE research. This analysis resulted in various suggestions for additional research projects. The analysis results also help map the scientific landscape and determine the direction of future research on customer engagement. This study also emphasizes the shift of CE research from traditional marketing methods to digital engagement strategies. Highly cited works and influential authors were also identified, demonstrating an essential role in developing theory. In addition, new topics such as disengagement and problems in implementing CE strategies still need to be researched. Visualizations of overlay and density reveal how research priorities have changed over time and how specific key keywords dominate the literature. This study provides practical insights for academics and practitioners and offers a reference to identify research gaps, recent subjects, and development opportunities in customer engagement.
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.
Bibliometric Analysis of Strategic Management and Meaningful Work: Trends, Collaboration, and Future Directions Sunardjo, Richard Andre; Riza Chakim, Mochamad Heru; Natalia, Ester Ananda; Rahardja, Untung; Sihotang, Sondang Visiana
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.v5i1.1088

Abstract

This study explores the evolution of Strategic Management and Meaningful Work (SDG-8) research through a bibliometric analysis of Scopus-indexed publications from 2015 to 2025. The aim is to map global trends, collaboration networks, and thematic clusters, thus enhancing understanding of how strategic management practices align with team member well-being and sustainable business models. Building on established literature in sustainable business, digital transformation, and ethical leadership, the research integrates human resource management and organisational behaviour theories. It examines how strategic management interacts with meaningful work, drawing on previous bibliometric and conceptual studies. A keyword-based search in the Scopus database identified 222 publications, refined to 110 English-language articles, conference papers, and reviews. VOSviewer software was used to construct co-occurrence networks and thematic maps across countries, organisations, authors, and keywords. The analysis reveals a significant increase in research output, with key hubs in the United States, Switzerland, Australia, and China. Influential institutions include MIT, Harvard T.H. Chan School of Public Health, and Wageningen University. Emerging themes such as digital transformation and competitive advantage underscore the growing integration of strategic management with meaningful work. These findings highlight the necessity for enhanced international collaboration to advance sustainable business practices and promote team member well-being.
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.

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