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The Bibliometric Analysis of Biofuel–Gasoline Research on Emission Performance and Material Durability in Combustion Systems Lubis, Putri Bintang; Najiha, Putri; Pramana, Yoddis
SPROCKET JOURNAL OF MECHANICAL ENGINEERING Vol 7 No 2 (2026): Edisi Februari 2026
Publisher : Program Studi Teknik Mesin, Universitas HKBP Nommensen, Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36655/sprocket.v7i2.2160

Abstract

This study aims to analyze the research development on biofuel–gasoline blends, focusing on emission performance and material durability within combustion systems through a bibliometric approach. Data were retrieved from the Scopus database covering the period 2022–2026, including 1,746 English-language documents in the Engineering subject area. The analysis was conducted using VOSviewer software to map publication trends, research themes, and author collaboration networks. The results show an increasing trend in publications from 2022 to 2025, indicating growing scientific interest in energy efficiency and carbon emission reduction. The thematic map identified four major clusters, with dominant themes such as biofuel, carbon dioxide, and life cycle, reflecting a shift in research orientation toward sustainable energy systems. Furthermore, the co-authorship network revealed strong collaborative links among researchers, particularly from Asian countries such as China and India. Overall, this study highlights that research on biofuel–gasoline blends is evolving toward a globalized and sustainability-oriented framework, emphasizing efficiency, material resilience, and low-emission combustion technologies in support of the global clean energy transition.
Simulasi Monte Carlo untuk Analisis Kinerja Sistem Antrian pada Operasional Coffee Shop Skala Kecil Zharif, Erza Arkan; Lubis, Putri Bintang; Najiha, Putri; Abdillah, Akbar; Mutiara, Tasya Dewi
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 1 (2026): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i1.55849

Abstract

This study aims to analyze the performance of a queueing system in a small-scale coffee shop operation using the Monte Carlo simulation method based on historical data from 2022–2026. Coffee shop operations exhibit stochastic characteristics influenced by fluctuations in customer arrivals and service time variability. Data on daily visitors, revenue, cost, and profit were processed using Microsoft Excel to construct empirical probability distributions. The simulation was executed through thousands of iterations to ensure statistical stability. The results indicate that the model effectively captures operational uncertainty, with convergent average daily profit and measurable downside risk assessed through percentile analysis and Value at Risk (VaR). The findings provide an analytical foundation for managerial decision-making regarding service capacity and cost control strategies. Monte Carlo simulation proves to be an effective tool for performance evaluation and risk management in small-scale service businesses.