cover
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
ISSN : -     EISSN : 27752674     DOI : -
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
Articles 80 Documents
Search results for , issue "Vol 5, No 1 (2025)" : 80 Documents clear
Supporting Application Fast Learning of Kitab Kuning for Santri' Ula Using Natural Language Processing Methods Zaman, Qamaruz; 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.v5i1.713

Abstract

Education in Islamic boarding schools is one of Indonesia's traditional forms of education that teaches Islamic religious teachings, including studying the yellow classic books as the primary source of spiritual learning. However, learning the Yellow classic book is often complicated by 'ula students (early level students) because Arabic is without harakat or lines, and the material studied is very complex. To overcome these challenges, this research aims to develop a yellow Islamic classic book learning support application for 'ula students using the Natural Language Processing (NLP) method. This application has an interactive chatbot feature that helps students understand the contents of the yellow book more effectively and enjoyably. The research method includes literature study, data collection, data processing, and system development using the Sparse Categorical Cross Entropy algorithm in Natural Language Processing to improve the accuracy of chatbot responses. This application provides an innovative solution by presenting an interactive learning experience that can be accessed anytime and anywhere, thus facilitating Santri learning outside the boarding school environment. The results show that learning for 'ula students with the Natural Language Processing method is very good and easy to understand. The test shows that the accuracy of the application reaches 100% with a low error value (loss), which is 0%. It can be recognized that the effectiveness of Natural Language Processing in supporting yellow book learning, maintaining the tradition of Islamic education in the digital era, and helping teachers and parents monitor the development of students.
Implementation of Committee Partnerships on AI-Based School Policies at Public Junior High School Mulatiwi, Tri; Supriadi, Didi; Mulyanto, Rahmat
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.627

Abstract

In the increasingly sophisticated digital era, artificial intelligence (AI) technology has significantly changed various fields, including education. In Indonesia, secondary schools have begun implementing AI technology to improve the quality of teaching and school management. Implementing this technology includes using AI-based systems for personalized learning, student data analysis, and more efficient school administration management. Implementing AI-based policies requires a strong partnership between the school committee and the school. This includes monitoring technology implementation, providing teacher training, and involving parents in the technology-based learning process. This study aims to identify and analyze the role of partnerships between school committees and schools in implementing AI-based policies at SMP Negeri 3 Tanjungsari. To ensure effective policy implementation, various stakeholders, including school committees, must support advancing AI technology in education. This study employs a qualitative approach, incorporating a case study method. It obtained the collected data through in-depth interviews, participant observation, and document analysis. The study results indicate that strong partnerships between school committees and schools play a significant role in supporting the implementation of AI policies. However, some challenges are still faced, such as the committee's lack of understanding of AI technology. This study also offers strategies to improve the effectiveness of these partnerships, including training and enhancing communication between the committee and the school. These findings significantly contribute to developing educational policies that are more adaptive to technological advances.
The Effect of Carbon Nanotubes on the Marshall Characteristics of AC-WC Asphalt Mixture Akbar, Said Jalalul; Maizuar, Maizuar; Muthmainnah, Muthmainnah; Ersa, Nanda Savira; Desmi, Adzuha; Arfiandi, Joni; Adha, Ridwan; Larasati Putri, Ditya
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.v5i1.690

Abstract

Carbon Nanotubes (CNTs) are cylindrical nanostructures with exceptional mechanical strength, high electrical conductivity, and excellent heat transfer capabilities, making them a promising additive in asphalt mixtures. This study investigates the effect of CNTs on the Marshall parameters of Asphalt Concrete-Wearing Course (AC-WC) mixtures using 60/70 penetration asphalt. CNTs were added to asphalt at 60°C, followed by coarse and fine aggregates preheated to 150°C. Marshall parameter tests were conducted on the samples, and the results showed a significant increase in stability compared to conventional asphalt. Asphalt stability increased by 9%, with the highest value obtained at a CNT concentration of 0.015%, reaching 2177.83 kg. The optimal stability was achieved at a CNT concentration of 0.015%. This study demonstrates that CNTs can be effectively utilized to enhance the performance of AC-WC asphalt mixtures. The flow values decreased as the CNT content increased because CNTs make the asphalt mixture stiffer, improving temperature resistance.
Comparative Analysis of Tensile Strength of Steel Tubing Pipe Welding Results Using SMAW and MIG Welding with 140A Current Tri Aulia, Yuni; Ariyon, Muhammad; Fitriani, Fitriani; Sebayang, Alexander; Tarigan, Efrata
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.v5i1.645

Abstract

Welding is a crucial technology in modern manufacturing processes, widely applied in automotive, oil refineries, and other industries. This study focuses on two standard welding techniques: Gas Metal Arc Welding (GMAW) and Shielded Metal Arc Welding (SMAW). GMAW uses argon gas as a shielding gas, and the ER70S-6 electrode has a 1.0 mm diameter, while SMAW employs the E7018 electrode with a 2.6 mm diameter. Both methods are tested on ASTM 106 Grade B steel, a commonly used material in various industries. The primary goal of this research is to evaluate the tensile strength of steel specimens welded using MIG and SMAW. The tensile strength of raw material, as well as the welded materials, is measured to assess the quality of the welds. The results show that the tensile strength of the raw material is 648.26 kgf/mm². After welding, the tensile strength for the MIG-welded material is 540.79 kgf/mm², while the SMAW-welded material achieves a higher tensile strength of 616.17 kgf/mm². These values highlight the significant difference in performance between the two welding techniques. SMAW welding provides the best joint quality among the two methods, with a tensile strength value of 616.17 kgf/mm². This study underscores the importance of selecting the appropriate welding technique based on the desired strength and application, with SMAW proving superior for this particular material. These findings contribute valuable insights into material technology and welding, offering a reference for future industrial applications.
Gold Price Prediction Using Long-Short Term Memory Algorithm Based on Web Application Dalimunthe, Rodiatul Adawiyah; Adek, Rizal Tjut; Agusniar, Cut
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.v5i1.724

Abstract

Gold is a significant investment asset, particularly in times of economic instability. Various factors, including decisions by financial authorities, inflation, and global economic dynamics, influence the fluctuations in gold prices. Accurately predicting gold prices is valuable for investors when making investment decisions. This study aims to utilize the Long Short-Term Memory (LSTM) algorithm for predicting gold prices and develop a web-based application connected to Yahoo Finance to acquire real-time gold price data. The LSTM algorithm was chosen because it handles time series data with long-term dependencies. LSTM has an architecture that allows the model to retain relevant information over long periods and forget irrelevant data. In this study, the developed LSTM model produced a Mean Absolute Error (MAE) of 19.81, indicating that the average prediction deviates by approximately 19.81 units from the actual value. Furthermore, an average Mean Absolute Percentage Error (MAPE) of 0.83% demonstrates the high prediction accuracy. The results of this study show that LSTM is an effective method for predicting gold prices. The resulting web application allows users to access gold price projections interactively, thereby assisting investors in making more accurate and data-driven decisions with easy access. Additionally, the web application offers customizable features such as adjusting prediction parameters and visualizing results in real time.  These features not only enhance user engagement but also improve decision-making processes. This research provides a practical tool for optimizing investment strategies in a dynamic economic environment by leveraging machine learning and seamless web integration.
Development of Plastic Shredder Technology to Support Plastic Waste Reduction Harjuma, Harjuma; Tahir, Abdul; Sirama, Sirama; Aswar, Aswar
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.v5i1.643

Abstract

The plastic waste problem in Indonesia has reached a severe level. Data from the National Waste Management Information System shows that Indonesia produces around 17 million tons of plastic waste yearly. However, only approximately 66.47% of this plastic waste undergoes recycling, with the remainder ending up in landfills or polluting the sea. This condition places Indonesia in second place in the world after China in terms of the amount of plastic waste produced, making it a country with a plastic waste emergency. This article discusses the development of plastic recycling machine technology as a solution to overcome the plastic waste problem in Indonesia. With a production of around 17 million tons of plastic waste per year, Indonesia faces significant challenges in plastic waste management. Low efficiency often constrains the effectiveness of plastic recycling as a solution. Therefore, this study aims to design and improve the efficiency of a plastic shredder machine. This machine uses specially designed rotating blade technology to produce high-precision plastic flakes. Additionally, we have updated the transmission system to reduce vibration and implemented other innovations to enhance the machine's capacity to shred various types of plastic. We expect this machine to decrease greenhouse gas emissions from the recycling process and lower operational costs. This study shows that the developed plastic shredder machine can work effectively and efficiently, meeting the research objectives of producing plastic flakes quickly. Thus, we expect this machine to significantly reduce plastic waste in Indonesia and support environmental conservation efforts.
Corona Discharge Detection Analysis on Aluminum and Iron Conductors by Point Field Electrode Method Nugroho, Satrio Dwi; Setiabudy, Rudy; Negara, Roy Bayu; Aliffianti Ulfiah, Shindy; Azhary Arsal, Fanji
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.v5i1.706

Abstract

Currently, Southeast Asia's highest primary energy usage is in Indonesia. Electrical infrastructure like transmission and distribution will be directly responsible for the high energy use. More distribution electrical networks will be in place due to the growing demand for electricity. So, the more significant the electrical disruptions that arise. Corona is one type of electrical disruption in the medium voltage network system. Corona is caused by a partial release of electrical charge, meaning the charge does not entirely pass through both conductors. The surrounding air experiences dielectric stress, producing noise, purple light, and a characteristic smell. Corona's appearance may seriously affect electrical equipment. Additionally, there are other ways to identify the appearance of corona, including using the senses of sight, smell, and hearing. The hearing approach involves utilizing a sound-capable sensor to detect corona. By taking pictures of the location of the corona, one can use sight to detect it. On the other hand, an ozone gas sensor is used in the scent approach. The author attempted to use the method of scent in this investigation. An ozone sensor will record corona disruptions that occur at the delivery site. Oxygen can be broken down into ozone because the air around the corona may ionize the surrounding air.
Performance of K-Nearest Neighbor Algorithm and C4.5 Algorithm in Classifying Citizens Eligible to Receive Direct Cash Assistance in Bandar Mahligai Village Chaliza Nur, Wan Amalia; Abdullah, Dahlan; 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.v5i1.752

Abstract

Direct Cash Assistance, commonly called BLT, is one of the many programs the Indonesian government held to reduce the poverty rate of the Indonesian population. This study compares the KNN and C4.5 methods to determine the eligibility of residents eligible to receive Direct Cash Assistance in Bandar Mahligai Village. This study began with collecting resident data from the Bandar Mahligai village office. Then, the data obtained was taken into several attributes to be used in the classification process, namely the name of the head of the family, KK number, NIK, number of dependents, occupation, income, and monthly expenses. After the data is collected, the data will be classified using the KNN and C4.5 algorithms. There is a significant difference between the two algorithms in the classification process; the KNN algorithm by looking for the nearest neighbor data value, in this study, the K value = 9, while the C4.5 algorithm by building a decision tree from the attribute values taken based on resident data used as training data. The classification results of the two methods will be compared using a confusion matrix to obtain a higher accuracy technique. The results of testing using a confusion matrix for both algorithms are the accuracy produced by the KNN and C4.5 algorithms in classifying residents eligible for Direct Cash Assistance (BLT) of 90% in the system that has been built. The results of comparing the KNN and C4.5 algorithms for this study show that the KNN algorithm is better because the accuracy level reaches 90% in manual and system calculations. While the C4.5 method only gets 85% for the accuracy of its manual calculations, it receives an accuracy level of 90% in the system that has been built.
Designing for Digital Influence: The Impact of Gigi Susu's Facade on Social Media Branding Canny Utami, I Gusti Ayu; Yogik Adnyana Putra, I Wayan; Ardiarani Utami, Ni Wayan
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.v5i1.784

Abstract

This research explores the impact of interior design, specifically the façade and interior features of Gigi Susu café, on its brand identity and success in social media branding. The study examines how the café's design elements—such as facade, signage, and natural aesthetics—contribute to its visibility on platforms like Instagram and shape customer perceptions of the brand. Using a mixed-methods approach, including content analysis of Instagram posts, customer surveys, and observational studies, the research investigates the role of "Instagrammable" design in fostering user-generated content (UGC) and customer engagement. Findings suggest that the café's visually distinctive and shareable design has enhanced brand recognition, positioning Gigi Susu as a prominent brand in Bali's competitive café market. The study concludes that facade design plays a crucial role in modern branding, emphasizing the need for businesses to consider both physical experiences and digital engagement in their design strategies. By aligning physical spaces with social media culture, companies can leverage design as a powerful digital influence and brand amplification tool.
Implementation of Complex Proportional Assessment Method in Determining Prioritization of Beneficiary Groups Fish Seeds in Lhokseumawe City Ramadhani, Putri Yesi; Safwandi, Safwandi; 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.v5i1.754

Abstract

The fisheries sector in Lhokseumawe City has an essential role in the regional economy, but the limited allocation of fish seed assistance requires an efficient and objective decision-making system (SPK). This research applies the Complex Proportional Assessment (COPRAS) method to prioritize groups of fish seed aid recipients. COPRAS was chosen because it can handle quantitative and qualitative criteria and produce a clear ranking of alternatives. The system evaluates criteria such as pond area, number of members, pond condition, and group age. The results showed that the Tani Mandiri group had the highest utility value = 1, while Tani Maju Berkah obtained the lowest value = 0.655. The COPRAS method effectively provided accurate and transparent recommendations in determining beneficiaries. Implementing this system is expected to help the Lhokseumawe City Marine, Fisheries, Agriculture, and Food Service Office allocate fairer and more targeted assistance, as well as increase the fisheries sector's productivity in the area. This research also contributes to developing technology-based decision-making systems to support government policies.