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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 134 Documents
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THE DESIGN AND DEVELOPMENT OF A BANJAR ADAT WEBSITE AS A DIGITAL IMAGE OF SOCIAL LIFE IN BALINESE COMMUNITIES Bagus Putu Pramana Putra; I Kadek Widiantara; I Putu Gede Budayasa; I Dewa Gede Agung Pandawana
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

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Abstract

The rapid advancement of information technology has driven the need for digital transformation in traditional communities, including Banjar Adat in Bali, which plays a central role in regulating social and cultural life. However, the absence of structured digital media has limited the effectiveness of information dissemination, documentation, and representation of cultural identity. This study aims to design a conceptual model of a website-based information system as a digital representation of the social life of Banjar Adat communities. The research adopts a Research and Development (R&D) approach with a qualitative method in the needs analysis phase. Data were collected through observation, interviews, and documentation involving banjar administrators and community members. The system design process employs a prototype approach, including user needs analysis, system structure design, user interface (UI/UX) design, and feature modeling such as banjar profiles, activity calendars, announcements, and documentation galleries. The results of this study are in the form of a conceptual system design and interface prototype that align with user needs and reflect local cultural values. The findings indicate that the proposed design can serve as a foundational model for developing a website that functions both as an information medium and as a digital image of social life in Balinese communities.
Intelligence at the Vault: How Machine Learning is Revolutionizing Banking, Credit Risk & Fraud Detection. An In-Depth Analysis of Machine Learning Applications for Banking and FinanceThe financial services sector stands at an inflection point, driven by Rishabh Vinod Kumar Dubey; Dr. Ravinder Singh Madhan
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 1 (2026): March
Publisher : PT. Radja Intercontinental Publishing

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Abstract

The financial services sector stands at an inflection point, driven by the rapid proliferation of machine learning (ML) technologies that are fundamentally reshaping how banks and financial institutions operate. This research paper presents a comprehensive in-depth analysis of the integration of machine learning in banking and finance, with a focused examination of two primary objectives: (1) enhancing credit risk assessment mechanisms, and (2) improving fraud detection and prevention systems. Drawing on data from over 120 global financial institutions, peer-reviewed literature, and empirical case studies spanning 2018 to 2024, this paper investigates how ML algorithms — including Random Forest, Neural Networks, Support Vector Machines, Gradient Boosting, and Deep Learning architectures — have transformed traditional banking paradigms. Our findings indicate that ML-powered credit risk models achieve accuracy rates of up to 92%, outperforming conventional statistical models by 15-20 percentage points. In fraud detection, ML systems demonstrate detection accuracy of 96%, with false-positive rates reduced by up to 60%. The paper further explores implementation challenges such as data quality issues, model interpretability, regulatory compliance under Basel III/IV frameworks, and ethical considerations including algorithmic bias. Recommendations for responsible ML deployment are provided, alongside projections for future developments including explainable AI (XAI) and federated learning in financial contexts.
IMPLEMENTATION OF DESIGN THINKING FOR THE DIGITAL TRANSFORMATION OF DESA CANTIK MENTORSHIP AT BPS-STATISTICS TANGERANG REGENCY Reza Septian Pradana
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

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Abstract

Village for Statistical Excellence or Desa Cinta Statistik (Desa Cantik) program is a sectoral statistical development program implemented by the BPS-Statistics Indonesia to improve literacy, data management quality, and statistical utilization at the village level. However, the implementation of face-to-face statistical development still faces various obstacles, such as limited learning time, a work environment full of interruptions for village officials, difficulty repeating material, and limited access to flexible learning media. This study aims to design a digital transformation of Desa Cantik development program at the BPS Tangerang Regency using a design thinking approach. The study used a qualitative approach with the stages of understand, observe, define point of view, ideate, prototype, test, and reflect. Data collection was conducted through in-depth interviews, observation, documentation, and usability testing with village statistical agents assisted by BPS Tangerang Regency. The results showed that village statistical agents need statistical learning media that is simple, flexible, easily accessible, and can be re-learned independently. Based on the results of the ideation and testing process, a prototype of an Android-based e-learning application called StaT-Gem (Statistik Tangerang Gemilang) was developed, which features short learning videos, a structured material repository, an offline mode, and light quizzes with positive feedback. Usability testing results indicate that the application is easy to use, has intuitive navigation, and can help users access learning materials more flexibly according to the working conditions of village officials. This study concluded that the application of design thinking can produce digital transformation solutions that are more adaptive to user needs and support the sustainability of Desa Cantik's statistical development through an effective and user-centered e-learning approach.
Intelligent Finance: A Comprehensive Analysis Of Machine Learning Transforming Banking, Credit Risk & Fraud Detection Rishabh Vinod Kumar Dubey; Dr. Ravinder Singh Madhan²
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

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Abstract

The integration of machine learning (ML) into banking and financial services represents one of the most significant technological transformations of the 21st century. This research paper presents an in-depth analysis of how ML algorithms and models are reshaping core banking operations—with a focused examination of two critical objectives: enhancing credit risk assessment and improving fraud detection and prevention. Drawing on empirical data, industry case studies, comparative model evaluations, and forward-looking projections, this paper demonstrates that ML-driven systems consistently outperform traditional statistical methods in accuracy, speed, and adaptability. The findings underscore the urgent need for financial institutions to adopt robust ML frameworks, while also addressing challenges related to model interpretability, regulatory compliance, and ethical deployment.

Page 14 of 14 | Total Record : 134

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