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 593 Documents
 25   26   27   28   29 
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.
Expert System For Diagnosis of Mental Health Disorders in Students Using Case-Based Reasoning Method With a Web-Based Positive Psychology Approach Bancin, Udurta; Bustami, Bustami; Rosnita, Lidya
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.v4i4.592

Abstract

Mental health issues among students have become a significant concern affecting their quality of life and academic performance. An effective expert system is needed to diagnose and provide appropriate interventions. This research develops a web-based expert system that utilizes the Case-Based Reasoning (CBR) method combined with a positive psychology approach to diagnose mental health disorders in students. The CBR method identifies similarities between new and previous cases, while the positive psychology approach focuses on individual strengths and potential for growth. The system integrates a database of student mental health cases and CBR algorithms to produce relevant diagnoses. This study investigates four types of mental health disorders: panic, anxiety, stress, and depression. The method used for data analysis is Case-Based Reasoning. The diagnosis results are based on calculations from symptom choices within the system, where each symptom has a weight. The highest similarity calculation obtained from past cases is used as a solution to address the problem. System testing, based on expert knowledge with 15 test data samples categorized by mental health disorders and 38 symptoms, achieved an accuracy rate of 85%.
Heigh Detection System Using Russel and Rao Method Hakim, Jamaludin; Tonggiroh, Mursalim; Nurhayati, Siti; Nur Hidayat, M. Ali; Sah, Andrian
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.v4i4.671

Abstract

Height detection is an exciting area of research with broad applications in fields such as construction, healthcare, and robotics, where measurements are still often done manually. This research aims to automate the height calculation process by developing a height detection system using image processing techniques, which offers improved accuracy and efficiency. The system that will be built works by capturing images of objects through a webcam and using the Russel Rao cluster analysis method to calculate height later. Borland Delphi 07 was chosen as the programming language because of its ability to handle image-processing tasks. This research draws on a thorough literature review of various books and articles, with the system operating in stages, starting with converting images to grayscale to simplify the data for more accessible analysis and then followed by applying Russel Rao's method for height measurement. However, the system is sensitive to environmental factors around the object. The system will perform best when there are no other objects near the target because when there are other objects nearby, it can cause the measurement line to shift and interfere with the results. The detection system requires a controlled environment with no foreign objects nearby for optimal performance. Despite these limitations, Russel Rao's analysis method achieved an accurate detection accuracy of approximately 65%, with three out of eight sample tests yielding correct measurements. While this shows room for improvement if more relevant research is to be done in the future, this system will build a strong foundation for further development in this field. Future enhancements could focus on refining the algorithm to increase detection accuracy, make the system more resilient in dynamic or cluttered environments, and expand its potential applications in various fields.
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%.
Identification of Smart Environment Readiness in Realizing Smart City Kotamobagu Nini, Wa; Anripa, Nuralfin; Alian, La Ode; Maulana, Muh Vikky
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.v4i4.646

Abstract

This study aims to identify the readiness of the innovative environment in realizing an intelligent city. A descriptive qualitative approach combined data collection techniques such as in-depth interviews, observation, and documentation. Primary data were obtained directly in the field through observation and interviews with diverse respondents. Secondary data were obtained from the Kotamobagu Environmental Service and the Kotamobagu PUPR Service. Data analysis was conducted through four stages: data collection, data reduction, data display, and conclusion drawing. The study results revealed that five innovative environment indicators were adequately met: the feasibility of water channels, irrigation channels, green space planning, water and air quality, and waste management systems. One indicator, the use of environmentally friendly energy resources, was not met. The study recommends that the Kotamobagu government develop policies or programs to build renewable energy resources to support the intelligent environment and realize Kotamobagu's smart city vision.
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.

Page 27 of 60 | Total Record : 593

 25   26   27   28   29 

Filter by Year

2021 2026


Reset
Filter By Issues
All Issue Vol 6, No 1 (2026) 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