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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
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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
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Search results for , issue "Vol 5, No 1 (2025)" : 80 Documents clear
Learning of McDonald’s Operation Management & Consumer Behavior Analysis: A Qualitative Study Nawangwulan, Irma M; Anantadjaya, Samuel PD; Agus Rachmat, Timotius
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.v5i1.687

Abstract

This paper will discuss the overall operation management and the typical characteristics or behaviours of McDonald's consumers. The aim is to demonstrate McDonald's ability to comprehend the diverse facets of consumer purchasing behaviour and effectively manage its operations to address all potential challenges. The research method in this paper uses a descriptive qualitative approach. McDonald's is a globally recognised company in the fast-food industry. The operational strategy of McDonald's is to cut costs, boost product quality, guarantee timely delivery to consumers, and innovate continuously to improve performance. Fast food giant McDonald's can keep expenses down because of careful management. McDonald's never compromises on the quality of its food or service to its consumers. Fast food giant McDonald's uses a just-in-time system to meet customer demands for quick service and high-quality food on the go. Marketing and advertising widely employ the AIDA model to delineate the stages of consumer buying decisions and elucidate how advertisements engage and involve consumers in purchasing. McDonald's advertising employs the AIDA model to draw in consumers and create captivating ads that consistently attract new customers. Examining McDonald's marketing pillars is fascinating, as they are a key indicator of global success. McDonald's has developed a formula of four key elements that effectively maintain a business, set clear objectives, and effectively communicate with its customers.
Application of Multiple Linear Regression Method for Predicting Fish Production Based on Cultivation Type Limbong, Hendra Putranta; Abdullah, Dahlan; Anshari, Said Fadlan
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.v5i1.717

Abstract

One of the contributors to Indonesia's economy is the fisheries sector, which has a high potential for development. Fisheries are a highly promising subsector for development in Indonesia's growth efforts. Based on data from the Central Bureau of Statistics of Dairi Regency, three types of aquacultures remain actively utilized in each subdistrict: ponds/freshwater ponds and paddy fields. This research aims to develop a fish production prediction system based on aquaculture types using the Multiple Linear Regression method. The accuracy of the prediction results will be measured using the Mean Absolute Percentage Error (MAPE). The results of this study indicate that in almost every subdistrict, especially pond aquaculture, the MAPE value is 20%, which means it has good accuracy. However, exceptions are found in the Siempat Nempu Hulu subdistrict, which has a MAPE value of 34.29%, and the Silahisabungan subdistrict, which has a MAPE value of 43.78%. Despite these values, they are still categorized as sufficient since they are 50%. The lower the MAPE value, the more accurate the prediction results. The findings of this research show that the multiple linear regression method can be considered correct. For future predictions, some results show negative values. For instance, in Silimapunggapungga subdistrict, a decline in production is predicted for 2024 with -114.779 tons and 2025 with -134.316 tons. The pessimistic prediction results are caused by the decrease in the X2 variable (area size), leading to a minor Y (production) value, potentially becoming negative if the contribution of X2 is no longer sufficient to balance the values of X1 (b1) and a. On the other hand, the Lae Parira subdistrict is predicted to experience an increase in production in 2024 by 87.024 tons and in 2025 by 84.380 tons. This system is implemented using the Python programming language. It is expected to help relevant stakeholders understand production trends and enhance the efficiency of fisheries resource management in the Dairi Regency.
Exploring of Canva in Improving Writing Skills in English Subjects Retnowati, Dwi; Mulyanto, Rahmat; 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.v5i1.629

Abstract

The advancement of technology and information has brought significant changes in various aspects of life, including education. One of the impacts of globalization is the advancement of technology and information. Globalization cannot be separated from the rapid development of information and communication technology, the primary supporting factor. Appropriate technology can increase student learning motivation, increase interaction between students and teachers, and facilitate access to information. Educators must consider technology in learning. To present engaging and innovative education, teachers are required to follow technological developments. The intention is to use technology to facilitate the learning process. This study aims to describe the implementation of Canva and analyze its impact on improving writing skills in English subjects at SMP PGRI Saptosari. This study uses a qualitative descriptive method. Data was obtained through observation, questionnaire completion, and documentation. Observations were carried out twice. The study's results indicate improved writing skills, particularly in creating procedure texts for English learning. The obtained data concluded that the creativity assessment indicator increased from the previous average of 64.68 to 85.10. The score jumped from the lesser to the excellent category by 20.42 points. The second increase in diction or word choice resulted in an average value increase from 61.31 to 78.4, moving from the less category to the sufficient one. The last is in the organizational text, which was initially 71.81 and increased to 79.40.
Sentiment Analysis of Customer Satisfaction Towards Shopee and Lazada E-commerce Platform Using the Random Forest Algorithm Classifier Dewi, Tursina; Asrianda, Asrianda; Afrillia, Yesy
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.v5i1.692

Abstract

In the digital era, e-commerce platforms like Shopee and Lazada have become the primary channels for online transactions in Indonesia, significantly shaping consumer behaviour and business strategies. This study analyses and compares consumer sentiment towards product reviews on these platforms, focusing on three prominent stores: Skintific, Originote, and Azarine. The research utilized a dataset of 4,500 comments collected from both platforms, with 3,600 comments allocated for training and 900 comments for testing. The sentiment analysis used a lexicon-based approach and machine learning techniques to ensure accuracy and reliability. The results reveal that the Skintific store achieved 88% positive sentiment on Shopee and 84.1% on Lazada. The Originote store recorded 81.4% positive sentiment on Shopee and 91.5% on Lazada, while the Azarine store achieved 87.8% on Shopee and 77.9% on Lazada. These findings highlight variations in consumer sentiment between platforms, which platform-specific features and user demographics may influence. This study provides valuable insights for businesses to tailor their marketing strategies and improve customer engagement on different e-commerce platforms.
Performance and Capacity Analysis of Pabringan Road in The City of Yogyakarta Dewi, Kemmala; Sidiq, Alif Lombardoaji; Nasirun, Achmad
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.v5i1.612

Abstract

This study aimed to ascertain the traffic volume, evaluate the performance and degree of saturation, and identify the service level category on Pabringan Road in Yogyakarta City. We surveyed to obtain primary data for the research method. We then analyzed the data using the Indonesian Road Capacity Manual 1997. According to the survey results, Pabringan Road experiences peak volumes of 792.1 pcu/hour in the morning, 979.3 pcu/hour in the afternoon, and 1103.3 pcu/hour at night. The road capacity calculation yielded a maximum capacity of 1185.52 pcu/hour. The speed on Pabringan Road decreased by 43.52% compared to the design flow speed of 23.72 km/hour, which was approximately 0.75. The analysis results indicate that during the morning peak hour, the level of service falls into category C, characterized by stable flow, increasing traffic density, and an increase in internal obstacles. During the afternoon peak hour, the service level falls into category D, indicating an approaching unstable flow and a high traffic volume. Changes in traffic flow conditions significantly impact the speed, even though it remains manageable. Moderate traffic density, fluctuations in traffic volume, internal traffic obstacles, and temporary obstacles can cause a significant speed reduction. High traffic interval obstacles significantly reduce traffic speed during the evening peak hour, causing drivers to experience short-duration congestion.
Prediction of Plantation Crop Production Based on Environment Using Linear Regression and Single Exponential Smoothing Methods Sari, Marlina; Abdullah, Dahlan; Maryana, Maryana
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.v5i1.669

Abstract

Indonesia, as an agrarian country, heavily relies on the plantation sector as a key driver of its national economy. One significant region contributing to this sector is West Aceh Regency, which consists of 12 districts and is renowned for cultivating five main plantation commodities: oil palm, coconut, rubber, coffee, and cocoa. This research aims to develop a plantation crop production prediction system to support efficient resource planning and management in this sector. The system employs Linear Regression and Single Exponential Smoothing (SES) with a smoothing constant (alpha) of 0.2. The system's primary objective is to analyze historical production data at the district level and generate reliable predictions of future production trends. Linear Regression models the relationship between time (independent variable) and production volume (dependent variable), effectively capturing long-term trends. SES complements this by addressing short-term fluctuations, applying a weighted average where recent data carries greater importance. Prediction accuracy is evaluated using the Mean Absolute Percentage Error (MAPE). Findings reveal that Linear Regression consistently achieves high accuracy, with MAPE values below 20% in most districts, particularly for coffee and cocoa. Conversely, SES demonstrates varying results, performing well in some cases, such as coconut production in Arongan Lambalek (MAPE 20%), but poorly in others, such as oil palm in Bubon (MAPE = 91.06%). In comparison, Linear Regression in Bubon yields a more moderate MAPE of 35.16%. The system is integrated into a user-friendly, web-based platform, accessible to stakeholders like farmers, policymakers, and government agencies. By offering actionable insights into production trends, it aids in mitigating risks, optimizing resource allocation, and enhancing plantation management efficiency. This research underscores the importance of predictive analytics in agricultural planning, with potential applications in other agrarian regions.
Application of Fuzzy C-Means and Borda in Clustering Crime–Prone Areas and Predicting Crime Rates Using Long Short Term Memory in Northern Aceh Regency Lubis, Syahrul Andika; Ula, Munirul; Retno, Sujacka
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.v5i1.747

Abstract

North Aceh is a district with diverse geographical conditions, ranging from vast lowland areas in the north stretching from west to east, to mountainous areas in the south. The average altitude in North Aceh is 125 meters. The district covers an area of 2,694.66 km² with a population of 614,640 people in 2022. The issue of crime in North Aceh District has caused significant discomfort among the community. According to data from the Central Bureau of Statistics (BPS) of Aceh Province, the number of criminal cases increased from 6,651 cases in 2022 to 10,137 cases in 2023. Using the Fuzzy C-Means clustering method, the data was grouped into three clusters: cluster 1 represents safe areas, cluster 2 represents moderately vulnerable areas, and cluster 3 represents vulnerable areas. For ranking using the Borda method, the Dewantara Police Sector ranked first for the physical aspect, while the Muara Batu Police Sector ranked first for the item aspect. As for predictions using the LSTM model, almost all subdistricts achieved MAPE values below 20%, indicating that the LSTM model is quite effective in predicting crime-prone areas. For example, Baktiya District recorded a MAPE value of 15.85% for the physical aspect, while the best result was achieved by Simpang Keramat District for the item aspect with a MAPE value of 0.00%. However, in Syamtalira Bayu District, the item aspect reached a MAPE value of 20.07%. Although the MAPE value for the item aspect in Syamtalira Bayu is relatively high, it is still considered acceptable as it remains below 50%.
Implementation of Simple Exponential Smoothing and Weighted Moving Average in Predicting Netflix Stock Prices Sadewa, Bima; Safwandi, Safwandi; 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.v5i1.708

Abstract

This study aims to develop a stock price prediction system for Netflix using the Simple Exponential Smoothing and Weighted Moving Average methods and evaluate the accuracy of both methods. The system provides future stock price estimates based on historical data and includes evaluation metrics such as Mean Absolute Error and Mean Absolute Percentage Error. The implementation results show that SES achieved an MAE of 4.40 and a MAPE of 1.08%, while WMA resulted in an MAE of 8.65 and a MAPE of 2.11%. These findings indicate that SES is more effective in predicting stock prices with lower error rates, particularly for stable historical data. In contrast, WMA is more responsive to short-term trends but less accurate overall. Based on the results, SES is recommended as the developed system's primary method for stock price prediction.
Utilization of Artificial Intelligence in Strengthening the Pancasila Student Profile Project Integrated with STEM Waluyaningtyas, Agnes Deta; Saryanto, Saryanto; Rejokirono, Rejokirono
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.v5i1.625

Abstract

As the essence of education, the curriculum will persistently undergo changes and renewal to align with societal needs and the ever-expanding global challenges. The integration of STEM and the Pancasila Student Profile Strengthening Project is essential in the context of education in Indonesia. By utilizing STEM, educators can contextually and relevantly teach Pancasila values, enabling students to comprehend scientific and technological concepts and incorporate these noble values into their daily lives. However, STEM learning in schools often faces challenges, such as limited resources, less innovative methods, and students' difficulties understanding abstract concepts. Technological advances have brought significant changes in various aspects of life in recent years. Artificial intelligence extends beyond computer science and informatics, permeating multiple disciplines. Educators can utilize the introduction of artificial intelligence (AI) in the education sector as a tool to enhance learning. AI is designed to process cognitive modeling of human thinking related to how a machine can record information, imitate, and modify automatically. Therefore, this study aims to investigate the integration of AI in P5 with STEM. We conducted this research at SMP Negeri 1 Purwosari using a qualitative approach. The research results demonstrate the use of AI in the integrated STEM P5 activities, beginning with activity planning, implementation, and evaluation. AI guides activity planning, integrates directly into technology, and functions as an automated assessment tool, delivering prompt and precise feedback. Therefore, overall, AI has outstanding potential to help improve the effectiveness of the learning process and introduce students to technology that will play an essential role in their future.
Mapping Technology Acceptance Research in MSMEs Rahmanda Putra, Rifki; Rahmat Jaya, Nono; Setiawan, Adi
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.v5i1.688

Abstract

MSMEs contribute significantly to the Indonesian economy but often face challenges in technology adoption. This research identifies factors and barriers to technology acceptance in MSMEs, aims to formulate support strategies, and highlights the role of all in increasing technology acceptance. The results are expected to provide practical solutions for the MSME sector. This research uses qualitative methods with bibliometric techniques using the Vosviewers application. Searches used keywords such as external stimuli, Obstacle, Opportunity, Challenge, Cognitive response, and Readiness. The idea was to search for articles via Publish or Perish with 762 articles, which were then processed using VosViewers. The analysis results found that scientific mapping and the possibility of future research regarding technology acceptance could be used as a recommendation variable for future researchers as a reference for subsequent articles.

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