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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 149 Documents
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COCONUT PLANTATION FIRES: A REVIEW OF DRIVERS, IMPACTS, AND MITIGATION STRATEGIES Felixtianus Eko Wismo Winarto; Diki Bima Prasetio; Bambang Hari Priyambodo
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21338469

Abstract

Fires in coconut plantations, especially on tropical peatlands, cause serious environmental and economic problems. While most studies focus on oil palm, this literature review summarizes the causes, impacts, prevention methods, and restoration strategies specific to coconut plantations. The review shows that fires are mainly triggered by cheap land-clearing practices and the accumulation of dry wastes like husks and fronds, which become highly flammable during El Niño droughts and over-drainage. These fires cause direct palm mortality, reduce crop yields for up to three years, cause peat subsidence, and generate dangerous smoke haze that harms public health. To prevent these fires, strategies like proper water management, community involvement, and satellite or drone monitoring are essential. For post-fire recovery, maintaining the surviving coconut canopy and using coconut fiber as mulch offer cost-effective ways to restore soil and biodiversity. In conclusion, managing fires requires a combination of better waste management, water control, and active community participation.
COMPRESSIVE STRENGTH AND WATER ABSORPTION OF SCC MORTAR PAVING BLOCKS BASED ON LOW-VOLUME FLY ASH MODIFIED WITH CORN COB ASH Harsan Ingot Hasudungan; Muh. Samsunar Fajar
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

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Abstract

This experimental study investigates the compressive strength, water absorption, and workability of self-compacting concrete (SCC) mortar paving blocks incorporating low-volume fly ash (LVFA) and corn cob ash (CCA). Fly ash and corn cob ash were used at proportions of 0%, 5%, 7.5%, and 10% of the total cement mass. Compressive strength was evaluated at 7, 14, and 28 days, while water absorption and slump-flow tests were also conducted. The results indicate that increasing fly ash content improves slump-flow and enhances the flowability of fresh SCC mortar. In contrast, increasing corn cob ash reduces slump-flow because its fine, absorptive particles increase water demand. Considering mechanical performance and workability, the optimum mixture contained 10% fly ash and 5% corn cob ash. It achieved compressive strengths of approximately 29.45 MPa at 7 days, 34.65 MPa at 14 days, and 36.57 MPa at 28 days. Water absorption decreased from 5.21% at 7 days to 4.20% at 14 days and 3.00% at 28 days. The results demonstrate the potential of combining LVFA and corn cob ash in durable SCC mortar paving blocks while supporting the beneficial use of industrial and agricultural waste.
SPATIAL DISTRIBUTION ANALYSIS OF ELEMENTARY SCHOOL POINTS USING GIS-BASED POISSON MODEL Rahmat Idhami; Rian Farta Wijaya; Andri Saputra; Taufa Fadly; Hengki Gunawan; Ryan Fahreza Pasaribu
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21523278

Abstract

The equitable distribution of basic education facilities is an important indicator of fair regional planning. This study analyzes the spatial distribution pattern of Elementary School (SD) points in Bener Meriah Regency, Aceh Province, and models the number of schools against regional sub-district characteristics using a Geographic Information System (GIS) approach integrated with Poisson regression. School data were obtained from the Indonesian Ministry of Education's reference database (Dapodik), covering a full census of 143 SD-equivalent schools across 10 sub-districts, with a stratified random sub-sample of 34 geocoded schools used for point pattern analysis. Spatial pattern was assessed using Average Nearest Neighbor (ANN) analysis, while the effect of population on school count per sub-district was modeled using Poisson regression with area as an exposure offset. The ANN result yielded a ratio of R = 0.80 (z = -2.24; p < 0.05), indicating a statistically significant clustered pattern. The Poisson model across 10 sub-districts showed population to be a significant positive predictor of school count (IRR = 1.086 per 1,000 people; p < 0.001), although overdispersion was detected (deviance/df = 6.93), suggesting a Negative Binomial model for future work with a larger number of analysis units. These findings indicate spatial inequality in elementary school provision across sub-districts that warrants attention in education facility planning in Bener Meriah Regency.
THE USE OF GENERATIVE AI TO OVERCOME CREATIVE BLOCKS A CASE STUDY ON THE SPEED OF VISUAL CONCEPT DEVELOPMENT AMONG VISUAL COMMUNICATION DESIGN STUDENTS AT BUDI LUHUR UNIVERSITY Dela Maria Putri; Arief Ruslan
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 2 (2026): June
Publisher : PT. Radja Intercontinental Publishing

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Abstract

Students of Visual Communication Design (VCD) frequently experience creative block, which hinders the ideation and visual conceptualization process, particularly during the early stages of design development. This study aims to measure the effectiveness of Generative AI in accelerating the acquisition of visual concepts and mitigating creative block among VCD students at Universitas Budi Luhur. The research employs a mixed-method approach with an explanatory sequential design, involving 24 active students from semesters 2 to 8 selected through purposive sampling. Data collection was conducted through Likert-scale questionnaires, time-tracking experiments, observations, and in-depth interviews. The experimental results show that the average time required to generate visual concepts using conventional methods is 86.13 minutes, whereas with Generative AI it decreases to 40.54 minutes, resulting in a time efficiency of 52.93%. Additionally, 66.7% of respondents reported experiencing creative block, and 90% of them confirmed that visual stimuli generated by AI helped them overcome ideation barriers more quickly. These findings indicate that Generative AI functions effectively as a creative partner that accelerates the ideation phase without replacing the designer’s curatorial role. The study recommends the structured integration of Generative AI into the VCD curriculum as an ethical and productive ideation support tool
UNCERTAINTY ANALYSIS OF PRESSURE GAUGE CALIBRATION: COMPARISON OF THE GUM AND MONTE CARLO METHODS Aidil Arief Ananta; Irsyadi Yani; Barlin
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 3 (2026): September - ON PROGESS
Publisher : PT. Radja Intercontinental Publishing

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Abstract

This paper presents a comparative uncertainty analysis of pressure gauge calibration using the Guide to the Expression of Uncertainty in Measurement (GUM) method and the Monte Carlo Simulation method. Pressure gauge calibration was conducted over a range of 0 to 25 bar to determine indication errors and their associated measurement uncertainties, which are vital for metrological traceability. The study evaluates several uncertainty contributors, including reference standard uncertainty, repeatability, resolution, zero deviation, and hysteresis. While the GUM approach utilizes a standard analytical framework based on linear approximations, the Monte Carlo method provides a probabilistic propagation of input distributions through 1,000,000 numerical iterations. The results demonstrate a high level of agreement between the two methods, with differences in expanded uncertainty remaining below 5% across the investigated range. Hysteresis and repeatability were identified as the dominant uncertainty components, particularly at higher pressure points. The findings confirm that the analytical GUM approach is reliable for this linear calibration model, while the Monte Carlo simulation serves as an effective complementary tool for validating complex or non-linear measurement problems.
PREDICTION OF SUSTAINABILITY OF FAMILY PLANNING PARTICIPANTS BASED ON DEMOGRAPHIC CHARACTERISTICS USING RANDOM FOREST Dara Fazila; Zahratul Fitri; Lidya Rosnita
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 3 (2026): September - ON PROGESS
Publisher : PT. Radja Intercontinental Publishing

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Abstract

Family Planning (KB) is one of the government programs aimed at controlling population growth and improving family welfare. However, some Family Planning participants discontinued the use of contraceptives, which may affect the success of the program. Therefore, this study aims to develop a prediction system for the continuity of Family Planning participants in Cot Girek District using the Random Forest algorithm. The study used 1,000 Family Planning participant records containing demographic, socioeconomic, and contraceptive-related attributes. After the data preprocessing stage, 998 records were used to construct the prediction model. The research involved data preprocessing, Random Forest model construction, and model evaluation using Hold-Out Validation and 5-Fold Cross Validation. The results showed that the Age of the Youngest Child attribute had the highest Gini Gain value of 0.3486, indicating that it was the most influential factor in predicting the continuity of Family Planning participants. The model achieved an Accuracy of 93%, Precision of 93.33%, Recall of 96.18%, and F1-Score of 94.74%, while 5-Fold Cross Validation produced an average accuracy of 97.40% with a standard deviation of ±4.95%. In addition, Black Box Testing confirmed that all system functions are operated according to user requirements. These findings indicate that the Random Forest algorithm can effectively predict the continuity of Family Planning participants and can be used as a decision-support tool to assist Family Planning officers in monitoring and providing more targeted assistance to participants.
CROSS-CULTURAL COMMUNICATION BETWEEN LOCAL AND NON-LOCAL PLAYERS ON THE CIREBON UNITED SOCCER TEAM Radja Djibrali; Farida Nurfalah; Dedet Erawati
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 3 (2026): September - ON PROGESS
Publisher : PT. Radja Intercontinental Publishing

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Abstract

The diversity of cultural backgrounds within a multicultural soccer team has the potential to influence communication patterns, cohesion, and the effectiveness of cooperation among players. This study aims to analyze the dynamics of intercultural communication within the cirebon united soccer team composed of players native to cirebon united and players from outside the region using the cultural inteligence (CQ) framework. This study employs a qualitative case study approach, utilizing participatory observation and in depth interviews with local players, players from outisde the region, and the coach. Data were analyzed thematically based on the four dimensions of CQ: metacognitive, cognitive, motivational, and behavioral. The results indicate that differences in regional language and accents during the initial stages of interaction have the potential to cause misunderstandings, however, these did not escalate into conflicts because they were managed through clarification of meaning, the use of indonesian as a common language in formal contexts, and the strengthening of informal interactions that fostered emotional closenes. The four dimensions of CQ operate simultaneously during training, matches, and social interactions, thereby forming adaptive communication patterns that support team cohesion and performance stability. This study contributes to the fields of sports communication by demonstrating that cultural inteligence functions not only as an individual competency but also as an integrative mechanism that shapes the effectiveness of collective communication within a multicultural regional level soccer team.
ERGO-SMART CONSTRUCTION AND SUSTAINABLE PROJECT MANAGEMENT FOR OPTIMIZING TEMPORARY HOUSING DESIGN POST-EARTHQUAKE IN PASAMAN BARAT REGENCY Barkhia Yunas; Mutia Alius; Ranti Mustika Putri
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 3 (2026): September - ON PROGESS
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21766927

Abstract

This study presents an integrated approach to optimizing post-earthquake temporary housing (Huntara) design in Pasaman Barat Regency, West Sumatra, Indonesia, through the application of Ergo-Smart Construction and Sustainable Project Management principles. Following the 2022 earthquake that damaged over 1,100 buildings, the urgent need for efficient, comfortable, and structurally sound temporary shelters became evident. This research employed a mixed-method approach combining field surveys, ergonomic analysis, structural modeling using ETABS software, and sustainable project management strategies. The study developed a 36 m² single-story temporary housing model featuring brick masonry walls reinforced with ferrocement overlay, practical columns, and ring beams designed to resist seismic loads in accordance with SNI 1726:2019. Structural analysis revealed that all stress components remained well below material capacity, with safety factors ranging from 2.68 to 13.7. Ergonomic evaluation confirmed compliance with international standards for spatial dimensions, ventilation, lighting, and accessibility. The modular design utilizing ferrocement overlay demonstrated a 25% acceleration in construction time while maintaining structural integrity. This research contributes a replicable, evidence-based shelter design framework integrating structural safety, occupant comfort, and construction efficiency for disaster-prone regions.
Machine Learning in Banking and Finance: A Systematic Analysis of Applications, Model Performance, Ethical Risk, and Regulatory Readiness Rishabh Vinod Kumar Dubey; Dr. Ravinder Singh Madhan
Bulletin of Engineering Science, Technology and Industry Vol. 4 No. 3 (2026): September - ON PROGESS
Publisher : PT. Radja Intercontinental Publishing

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Abstract

The banking and finance industry has entered a period of accelerated transformation as machine learning (ML) methods migrate from experimental pilots into core decision-making infrastructure. This paper presents an in-depth, literature-grounded analysis of how machine learning is reshaping credit risk assessment, fraud detection and prevention, algorithmic trading and portfolio management, and customer engagement in retail and commercial banking. Drawing on a structured review of foundational and contemporary studies, the paper traces the evolution of analytics maturity in finance from descriptive and predictive analytics toward prescriptive and real-time decision-making, and synthesizes comparative evidence on the performance of classical and modern ML architectures for credit scoring. The paper further examines the ethical, regulatory, and interpretability challenges that accompany ML adoption, including algorithmic bias, fairness, data privacy under regimes such as the GDPR, and capital-adequacy compliance under Basel III. A mixed-method research design is proposed and illustrated with representative tables and figures summarizing application-level adoption patterns, thematic distribution of the literature, and comparative model performance metrics. The analysis identifies persistent research gaps in interdisciplinary methodology, bias mitigation, real-time trading risk, model explainability, and financial inclusion, and concludes with a research agenda intended to guide the next phase of responsible machine learning adoption in banking and finance.

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