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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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Student Perceptions of the Implementation of Big Data in Sinergy as Learning Optimization at the Bali Institute of Design and Business Satrya Ramayu, I Made; Manurung, Handrean; Rachmadhan Amri, Muhammad Febrian; Mahendra, Gede Surya; Yoga Indrawan, I Putu
International Journal of Engineering, Science and Information Technology Vol 4, No 1 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i1.611

Abstract

The current digital era is characterized by exponential data growth, presenting unprecedented opportunities and challenges in extensive data analysis. Data's increasing complexity and volume demand more efficient and effective analysis methods. In overcoming this challenge, big data technology is an innovative solution in data analysis. Semantic technology enriches the data modeling process by providing deeper context and meaning and facilitates more intuitive and accurate analysis, which is critical in managing diverse big data. The use of big data is an essential aspect of the learning system in information technology, especially at the Bali Design and Business Institute. This research aims to describe the implementation of big data on the Synergy platform as an effort to optimize learning at the Bali Design and Business Institute based on a literature review. Information technology that continues to develop has changed the learning paradigm by adopting Big Data in the context of e-learning. Synergy, as an innovative e-learning platform, has the potential to use Big Data to increase the personalization and effectiveness of learning for students. This research takes a qualitative approach by analyzing relevant literature and discussing the use of big data in education and e-learning. This literature review aims to understand how implementing Big Data can influence learning interactions, academic decision-making, and the development of adaptive learning strategies in educational environments. The literature review results show that using Big Data in e-learning can strengthen the personalization of learning, improve academic predictions, and provide deeper insight into student learning behavior. The implications of this research provide a solid theoretical basis for developing strategies for implementing Big Data at Synergy so that it can support improving the quality of learning at the Bali Institute of Design and Business.
Predicting Electricity Consumption in Aceh Province Using the Markov Chain Monte Carlo Method Gavinda, Virza; Nurdin, Nurdin; Fajriana, Fajriana
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.v5i1.678

Abstract

Electricity is essential to nearly every aspect of modern life, from industrial sectors to household needs. In Aceh Province, the demand for electricity has consistently increased along with economic growth, urbanization, and population expansion. Various studies indicate that rising electricity consumption is closely linked to economic growth and industrialization. This study uses the Markov Chain Monte Carlo (MCMC) method with the Metropolis-Hastings algorithm to predict electricity consumption in Aceh Province. The research addresses the significant increase in electricity consumption driven by economic growth and urbanization in the region. Electricity consumption data from January 2018 to December 2022 was utilized as the basis for modeling. The results indicate a 32.4% increase in electricity consumption over the past five years. The predictive model achieved high accuracy with a Mean Absolute Percentage Error (MAPE) of 2.41%, demonstrating its reliability in forecasting future electricity needs. Projections through 2030 show a continuous increase, reaching 482 GWh by the end of the period. These findings are expected to support decision-making in sustainable energy planning and providing adequate electricity infrastructure in Aceh. This study highlights the effectiveness of the Me-tropolis-Hastings algorithm in handling complex data with high variability, providing valuable insights for long-term energy planning
Sentiment Analysis of Google Maps User Reviews on the Play Store Using Support Vector Machine and Latent Dirichlet Allocation Topic Modeling Zahrah, Violita Aditya; Nurdin, Nurdin; Risawandi, Risawandi
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.580

Abstract

These days, traveling is made easier by utilizing easily accessible online directions such as Google Maps. Google Maps provides real-time routes by displaying and presenting the closest routes that users can take. However, lately, the routes provided by Google Maps services often get users lost by presenting routes such as forests, narrow roads, and even dead ends. Therefore, this study aims to determine the level of user satisfaction and sentiment into two categories, namely positive and negative, based on reviews on the Google Play Store platform using the Support Vector Machine (SVM) algorithm and topic modeling using Latent Dirichlet Allocation (LDA) to find out the collection of topics that are the main topics of conversation by users regarding Google Maps services. The results of this study show that the SVM algorithm is feasible to use in sentiment analysis classification with an accuracy value of 86%, precision of 93%, recall of 53%, and f1-score of 52%. In addition, topic modeling is applied to generate coherence values for each topic, which shows that the higher the coherence value, the more specific the topic is. The highest coherence value generated in this study was two topic models with a coherence value of 35.15%, but this study took five with a coherence value of 33.39%. The five topic models to be applied in this study are selected because they have a good enough coherence value to identify the main topics and hidden topics in Google Maps user reviews with the Latent Dirichlet Allocation model. The topic model shows five aspects users often discuss: Google Maps route accuracy, system and service errors, navigation application directions, lost time history, and convoluted route provision.
Comparison of Bored Pile Capacity Based on Analytical Design and Pile Load Test – A Case Study Putri, Karina Meilawati Eka; Fatikasari, Aulia Dewi; Wibisana, Hendrata
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.v5i1.659

Abstract

This paper presents a comparative study of bored pile ultimate capacity based on analytical design and field tests. The object of this analysis is the bored pile foundation of the Sei Alalak Bridge in Banjarmasin, Indonesia. The analytical design of pile ultimate capacity was carried out using the empirical methods provided by Reese and O'Neill (1988) and Meyerhof (1976). The calculation of pile ultimate capacity using the empirical method is based on SPT data from four boreholes representing soil data in the abutment, tower, and counterweight zones. Two pile load tests were used to validate the analytical design: pile driving analysis (PDA) and the bi-axial load test Osterberg Cell (O-Cell). The pile ultimate capacity from the empirical method is then compared to field tests regarding pile shaft resistance and end-bearing capacity. The analysis results indicate that the empirical methods tend to underestimate the pile's ultimate capacity by 30–60%. The results reveal that the Reese and O'neill (1988) empirical method generates a significantly lower pile ultimate capacity than Meyerhof (1976). This indicates that the Meyerhof (1976) method gives a closer result of pile ultimate capacity than the field test. On the contrary, the Reese and O'Neill (1988) method is more consistent with the PDA test results. As a result, in this study, the Reese and O'Neill (1988) method is preferred over the Meyerhof (1976) method for predicting the ultimate capacity of a bored pile since it has been demonstrated to be more reliable in estimating the pile's ultimate capacity.
Implementation of Data Mining for Nutrition Clustering of Toddlers at Posyandu Using K-Means Algorithm Kamilah, Muna; Abdullah, Dahlan; Suwanda, Rizki
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.v5i1.718

Abstract

This study aims to determine the nutritional status of toddlers in the Peulimbang sub-district using a clustering method that can group toddlers based on their dietary indicators, such as gender (jk), age (u), height (tb), weight (bb), and upper arm circumference (Lila). By using data analysis techniques such as K-Means clustering, this study successfully identified several groups of toddlers with different nutritional statuses, ranging from malnutrition to good nutrition to obesity nutritional status. The data for this study were taken directly from the Peulimbang Health Center, and as many as 765 toddler data were collected from 16 villages in the Peulimbang area. The programming language used in this study is PHP, which functions in web development and is often used to process data sent via web formula, interact with databases, and manage user sessions. Based on the results of clustering with the K-Means method using Euclidean Distance as a measurement between points, toddler data has been grouped into three Clusters, namely C1, C2, and C3. Cluster C1 covers 22.81% of 147 malnourished toddlers, C2 covers 48% of 323 well-nourished toddlers, and C3 covers 29.19% of 205 obese toddlers. Based on the clustering results, improving nutrition education programs for parents is essential, especially in areas with poor or lacking nutritional status. This program can include counseling on the importance of balanced nutrition, nutritious cooking methods, and choosing the right Food for toddlers. Thus, this study is expected to contribute to improving toddlers' nutritional status and overall public health in the Peulimbang District area.
Student Literacy Through Library Visits and Gemini AI Programs at SD Negeri Potrobangsan 2 Yarmini, Yarmini; Supriadi, Didi; Purnami, Sri
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.v5i1.631

Abstract

People often say that literacy is the foundation for a person's lifelong education. Improving students' literacy skills is one of the main focuses in today's education world. Literacy, which includes reading, writing, and understanding information well, is an essential foundation in the learning process at all levels of education. Good literacy skills help students succeed academically and equip them with the critical and analytical thinking skills needed in everyday life. We need to consider literacy development because it is a fundamental ability that every individual must possess to navigate life in the future. This study aims to develop a strategy to improve the literacy of fifth-grade students at SD Negeri Potrobangsan 2 through a combination of library visits and the Gemini AI program. We expect library visits to cultivate students' interest in reading physical books, while the Gemini AI program serves as an interactive digital literacy medium to enhance students' learning experiences. This research approach uses a qualitative method with observation, in-depth interviews, and focus group discussions (FGD) as the primary instruments for data collection. The study results indicate that integrating traditional literacy learning with digital technology can improve students' literacy skills holistically. Students showed increased reading comprehension, higher involvement in literacy activities, and mastery of digital literacy skills. Implementing this strategy also increased motivation among students to read and utilize the library optimally. Therefore, elementary schools can apply this strategy as an effective literacy learning model.
Clustering Agricultural Productivity by Type and Results Using K-Medoids Method in Districts North Aceh Zahara, Mutia; Fuadi, Wahyu; Meiyanti, Rini
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.v5i1.699

Abstract

This research aims to develop a web-based application that can cluster sub-districts in North Aceh District based on the type and yield of agricultural productivity, focusing on increasing the ease of visualization and data analysis by users. The method applied in this research is K-Medoids, a clustering technique used to group sub-districts based on high, medium, and low harvest levels. The application will use data from the North Aceh District Agriculture Office, covering 2021 to 2023, including various food crops such as rice, corn, peanuts, green beans, cassava, sweet potatoes, and soybeans. This research will analyze the sub-district name, type of agriculture, year of production, planting area, and harvest area to identify clusters of sub-districts with similar agricultural yield patterns. The system is developed using the PHP programming language to facilitate implementation and data access by stakeholders. As an evaluation tool for clustering results, the Davies-Bouldin Index (DBI) is used to measure the quality of clustering results. The results of this study are expected to provide insights into agricultural productivity in North Aceh District and assist policymakers in designing more effective strategies to increase agricultural yields, especially in low-yielding sub-districts. In addition, this application also provides an interactive platform for users to analyze agrarian data quickly and efficiently.
Comparison of Rigid Pavement Planning Using PD T-14-2003 and NAASRA 1987 Methods in Industrial Areas Krisdiyanto, Aris; Dewi, Kemmala; Azis, Faruk
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.v5i1.613

Abstract

As vital infrastructure, roads are a means of transportation access and function as a distribution route for goods and services. Road pavement plays a crucial role in highway construction, necessitating proper planning according to Indonesian standards and planning criteria to ensure smooth land transportation and provide comfort and safety for its users. This study aims to provide information on road conditions, drainage dimensions, and construction costs. Planning is crucial in every road construction design, particularly for rigid pavement, based on survey data collected from the road section. Numerous methods exist for calculating the design value of rigid pavement. We use the Pd T-14-2003 method and the NAASRA 1987 method (National Association of Australian State Road Authorities) to plan rigid pavement thickness in the industrial area of PT. Bukit Muria Jaya Kudus. The Pd T-14-2003 method yielded a JSKN of 4x107 and a CBR of 35% for the subgrade, resulting in a plate thickness of 150 mm. While the Naasra 1987 planning method achieved a JSKN of 6x107 and a CBR of 35% for the base soil, a plate thickness of 160 mm was obtained with a value of K = 80 kPa/mm. The reinforcement planning using the Pd T-14-2003 and Naasra 1987 methods involves longitudinal reinforcement D10 mm at a distance of 150 mm and transverse reinforcement D10 mm at 250 mm. The drainage dimensions at the cross-section location are width x height (1 m x 1 m), and the guard's height is 0.2 m.
Comparative Analysis of K-Means and K-Medoids to Determine Study Programs Salamah, Salamah; Abdullah, Dahlan; Nurdin, Nurdin
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.v5i1.673

Abstract

Education is the main foundation for the advancement of civilization. A high level of education in society is directly proportional to the progress of that civilization. Higher education plays an important role in shaping quality human resources and contributing to community and national development. In today’s era of information and technology, data processing and analysis are key to understanding the development of study programs in higher education institutions. Clustering techniques are used to identify patterns and relationships in large and complex datasets, which are crucial in determining study programs at educational institutions. This research compares two popular clustering methods, K-Means and K-Medoids to determine study programs. The data used consists of odd semester grades of 87 students in the third-years of high school with 5 variables. The information of clusters is based on the minimum academic criteria of 18 study programs representing 7 faculties in Malikussaleh University and grouped into 5 clusters. The evaluation of clusters is conducted using the Davies-Bouldin Index (DBI). The result of the study indicate that K-Means algorithm has 5 clusters with cluster members of 31, 5, 13, 26 and 17, and a DBI value of 1,19010. Meanwhile, the K-Medoids algorithm has 5 clusters with cluster members of 33, 15, 17, 17 and 5, and a DBI value of 1,27833. Based on the DBI value, the K-Means algorithm demonstrates better cluster quality compared to the K-Medoids algorithm.
Design and Testing of a Web-Based Student Information Management System Pasaribu, Johni S; Argadikusuma, Ilham S
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.594

Abstract

Politeknik Piksi Ganesha is an institution of higher learning located in Bandung, Indonesia, specializing in engineering and technological curricula. The research's general objective is to describe the design and implementation of the web-based Student Information Management System (SIMS) to manage student data at Politeknik Piksi Ganesha Bandung. The functional and non-functional specifications are represented using Unified Modeling Language (UML) based on broad data collection through observation, interviews, and a literature review. It also entails black-box testing, which measures the system's performance against set criteria, focusing on the output without the details of its internal workings. The significant findings indicate that SIMS enhances highly administrative processes, accuracy in data, and good communication among stakeholders by applying clear UML diagrams of the system. This successful system development meets the institution's requirements and adds to the bar for other developments within the educational technology sector. The result has also emphasized the need for practical design methodologies and testing frameworks to develop reliable information systems to improve decision-making in academic institutions. The research has contributed significantly to the discipline because it has shown how different technological innovations can alleviate the problems surrounding managing student information at higher education levels.

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