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Bulletin of Engineering Science, Technology and Industry
Published by PT. RADJA INTERCONTINENTAL PUBLISHING
ISSN : -     EISSN : 30255821     DOI : https://doi.org/10.59733/besti
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering
Bulletin of Engineering Science, Technology and Industry | ISSN: 3025-5821 is a peer-reviewed journal that publishes popular articles in the fields of Engineering, Technology and Industrial Science. This journal is published 4 times a year, namely in March, June, September and December. We invite scientists, practitioners, researchers, lecturers and students from various countries and institutions to contribute to publishing their work and research results in the fields of Engineering, Technology and Industry.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 125 Documents
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MACHINE LEARNING ANALYSIS IN IMPROVING THE EFFICIENCY OF THE STUDENT ADMISSION DECISION MAKING PROCESS NEW AT PANCA BUDI MEDAN DEVELOPMENT UNIVERSITY M. Rasyid; Zulham Sitorus; Rian Farta Wijaya; Muhammad Iqbal; Khairul
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.62

Abstract

The decision-making process in admitting new students is a crucial aspect that can influence the quality and efficiency of academic administration in higher education. This research aims to analyze the role of Machine Learning methods, especially Support Vector Machines (SVM), in increasing the efficiency of the decision-making process for new student admissions at the Panca Budi Development University, Medan. The data used in this research includes information from the student admissions process for the odd semester of the 2022/2023 academic year, which includes various variables such as Registration Number, School of Origin, Registration Payment, and others. The data is divided into a training set (70%) and a testing set (30%). The Support Vector Machine (SVM) model that was built was evaluated using metrics such as accuracy, precision, recall, and F1-Score. The research results show that the SVM model achieves an accuracy of 100%, with high precision and recall for both classes. Precision for both classes reached 1.00, while recall for the minority class (class 1) reached 0.91, indicating excellent model performance in classification. The conclusion of this research is that the Support Vector Machine (SVM) model can significantly increase efficiency and accuracy in the decision-making process for new student admissions at the Panca Budi Development University in Medan compared to conventional methods. These findings indicate that the application of Machine Learning methods can provide substantial benefits in the context of academic administration.
ANALYSIS OF GOOGLE USER SENTIMENT TOWARDS UNIVERSITAS PEMBANGUNAN PANCA BUDI BASED ON REVIEWS GOOGLEUSING THE NAÏVE BAYES ALGORITHM M Imam Santoso; Rian Farta Wijaya; Zulham Sitorus; Muhammad Iqbal; Leni Marlina
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.63

Abstract

This thesis examines user sentiment towards Panca Budi Development University by utilizing Google reviews as the main data and using the Naïve Bayes algorithm for sentiment analysis. This research aims to understand the public's perception of the university through reviewing reviews available on the Google platform. The data used consists of user reviews collected from Google Reviews. The analysis process begins with data pre-processing, including text cleaning and tokenization, followed by the development of a Naïve Bayes model for classification of review sentiment into positive, negative, or neutral categories. The results of this analysis provide insight into the strengths and weaknesses of Panca Budi Development University from a user perspective, as well as identifying areas that require improvement. It is hoped that these findings can become a basis for the university to improve the quality of its services and reputation in the eyes of the public. This research also highlights the effectiveness of the Naïve Bayes algorithm in sentiment analysis, and contributes to further studies on sentiment analysis in the education sector
COMPARATIVE ANALYSIS OF NAIVE BAYES ALGORITHM AND C4.5 ALGORITHM IN SELECTING TYPES OF UMKM PRODUCTS IN BBPSDMP KOMINFO MEDAN TRAINING Alex Siregar; Leni Marlina; Khairul; Muhammad Iqbal; Andysah Putera Utama Siahaan
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.64

Abstract

This study compares the accuracy of the Naïve Bayes and C4.5 algorithms in determining the most suitable product types for Micro, Small, and Medium Enterprises (MSMEs) participating in the Digital Entrepreneurship Academy (DEA) training program at BBPSDMP Kominfo Medan. This study uses a dataset from DEA participants between 2021 and 2022. The analysis shows that the C4.5 algorithm has a higher accuracy compared to Naïve Bayes, indicating its better effectiveness in helping MSMEs choose product types. These findings suggest that C4.5 is more suitable for applications that require a high level of accuracy, especially in the context of this study. This study provides valuable insights into the selection of algorithms to support decision making in the MSME sector.
IMPLEMENTATION OF CLOUD COMPUTING ON APPLICATIONS MOBILE JOB INFO Resha Russita; Hari Toha Hidayat; Safriadi; Muhammad Nasir
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.66

Abstract

Job vacancy info mobile application has now become an important tool for job seekers in the digital era since the COVID-19 pandemic which recorded a significant spike in the number of unemployed people in Indonesia. In facing this challenge, cloud computing implementation is a crucial solution. This research aims to test performance using the stress testing method and test cloud services from Google Cloud Platform using the Quality of Service (QoS) method. The results show that the server can withstand loads of up to 7000 users simultaneously within 180 seconds or 3 minutes. QoS testing shows that cloud services from Google Cloud Platform achieve an average throughput of 1301.4 kbps with a packet loss rate of 0.54%, an average delay of 0.0019 ms, and an average jitter of 0.00 ms. These results confirm that the implementation of cloud computing in the mobile application of job vacancy information can improve efficiency and quality of service, in accordance with the demands of a dynamic labor market and facing a significant surge in users.
OPTIMIZATION OF WIFI NETWORK IN KUALANAMU INTERNATIONAL AIRPORT Hendra Harnanda; Andysah Putra Utama Siahaan; Leni Marlina; Muhammad Iqbal; Zulham Sitorus
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 4 (2024): December
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i4.67

Abstract

A reliable and efficient WiFi network is a crucial facility to support the activities of passengers and visitors at Kualanamu International Airport. This study aims to identify issues affecting WiFi network performance and provide optimization solutions based on technical analysis and user needs. Data collection was conducted by measuring network parameters such as throughput, delay, jitter, and packet loss across various strategic airport areas, including waiting rooms, departure terminals, and commercial zones. The analysis revealed key challenges, such as high user density during peak hours and uneven access point distribution. To address these issues, the study proposes optimization steps, including bandwidth capacity expansion, reconfiguration of network devices, and the adoption of advanced technologies like WiFi 6. Implementing these recommendations is expected to enhance the quality of the WiFi network at Kualanamu International Airport, improve user experience, and support overall airport operations effectively.
THERMAL ANALYSIS OF PHASE-CHANGE MATERIALS FOR ENERGY STORAGE APPLICATIONS Syed Yamin Qadri
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 4 (2024): December
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i4.68

Abstract

Phase-Change Materials (PCMs) are emerging as promising candidates for energy storage due to their ability to store and release significant amounts of thermal energy during phase transitions. This research focuses on the thermal analysis of various PCMs to evaluate their performance in energy storage systems. By examining key parameters such as latent heat capacity, thermal conductivity, and phase transition temperature, the study provides insights into the optimisation of PCMs for efficient energy management. Experimental and computational methods were employed to analyse different types of PCMs, including organic, inorganic, and eutectic materials. The results highlight the trade-offs between thermal performance, stability, and material cost, paving the way for their integration into applications such as building energy systems and renewable energy storage. The findings contribute to developing sustainable and efficient thermal energy storage solutions.
ADVANCED SIGNAL PROCESSING TECHNIQUES IN COMMUNICATION ENGINEERING Vikram Singh Parmar
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 4 (2024): December
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i4.69

Abstract

Advanced signal processing techniques have become integral to modern communication systems, enabling efficient data transmission, improved signal quality, and enhanced network performance. This study explores key techniques, including adaptive filtering, wavelet transforms, and multiple-input multiple-output (MIMO) processing, which address challenges such as noise interference, spectral efficiency, and multipath fading. The analysis highlights the theoretical principles and practical applications of these methods in wireless communications, satellite systems, and fibre-optic networks. Comparative evaluations demonstrate the superiority of advanced algorithms in mitigating errors, maximising throughput, and ensuring reliable communication. Experimental results and simulations validate the performance of these techniques under various channel conditions, showcasing their adaptability to dynamic network environments. The research concludes with insights into the future of signal processing, particularly its integration with machine learning and artificial intelligence, to drive the evolution of communication engineering.
IOT-ENABLED SMART CITIES: CHALLENGES AND INNOVATIONS IN URBAN INFRASTRUCTURE: Syed Tahir Ali Qureshi
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 4 (2024): December
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i4.71

Abstract

The rapid urbanisation and technological advancements have led to the emergence of smart cities, where the Internet of Things (IoT) plays a critical role in transforming urban infrastructure. IoT-enabled smart cities aim to enhance quality of life by leveraging interconnected devices, real-time data analysis, and automated systems. However, these advancements come with challenges such as data security, system integration, and infrastructural compatibility. This article explores the challenges and innovations associated with IoT-enabled urban infrastructure, focusing on transportation, energy management, waste management, and public safety. The article concludes with potential future directions for sustainable and efficient urban development.
USE OF CANVA APPLICATION IN LEARNING PANCASILA AND CITIZENSHIP EDUCATION Muhammad Kenzie; Hannan Rava Mahardika; Muhammad Faiz Hariy Nughroho; Muhammad Fabian Pratama
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 4 (2024): December
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i4.73

Abstract

Pancasila and Citizenship Education (PPKn) has a strategic role in shaping students' character in accordance with the values ​​of Pancasila. However, the abstract and normative nature of the material often leads to a lack of student interest. This study aims to explore the use of Canva application as a technology-based learning media in Civics subject. Using qualitative research methods, data was collected through interviews with subject teachers and analysis of students' poster assignments. The results showed that the use of Canva significantly improved students' understanding of Pancasila values ​​and honed 21st century skills such as creativity and critical thinking. Teachers assessed students' assignments based on content and design creativity, which helped students convey information in an interesting and relevant manner. Despite challenges such as limited internet access and technical skills, the app proved effective in supporting interactive learning. It is recommended that regular technical training and supporting facilities be provided to optimize the use of Canva in Civics learning.
DEVELOPMENT OF ARTIFICIAL INTELLIGENCE (AI) SYSTEMS FOR BUSINESS SYSTEM OPTIMIZATION Muhammad Yazid Syafiq; Indah Nur Afhiva; Yaga Taruma Tarigan; Syafina Almaira Nazmi Aswin Nasution; Fadly Ardian Syahputra
Bulletin of Engineering Science, Technology and Industry Vol. 3 No. 1 (2025): March
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v3i1.75

Abstract

The advancement of artificial intelligence (AI) technology has brought major changes in various fields including business. This study aims to analyze the potential for developing AI systems to optimize business processes in Indonesia using a literature review approach. This study highlights trends, benefits, and challenges in AI implementation and shows that AI can improve efficiency, productivity, and innovation. Although the application of AI in Indonesia is still in its early stages, its potential is very large, especially in logistics and e-commerce. However, challenges such as limited access to technology and low digital literacy are still the biggest obstacles. This study uses a systematic literature review (SLR) technique to explore the application of technologies such as machine learning (ML), natural language processing (NLP), and robotic process automation (RPA) to improve operational efficiency. This study shows that with the right implementation strategy, AI can help Indonesian companies compete in the global market and accelerate their digital transformation.

Page 6 of 13 | Total Record : 125

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