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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.
Optimasi Persediaan Toko Mainan Menggunakan Simulasi Monte Carlo untuk Menghadapi Ketidakpastian Permintaan Musiman Nasution, Rafa Adhitya Dharmawangsa; Pramana, Yoddis; Lubis, Hasyim Fadhillah; Hasibuan, Ridho Rahman; Anwar, Khairul
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.v9i1.55900

Abstract

This study aims to optimize inventory policy in a toy retail store facing seasonal demand uncertainty using Monte Carlo simulation. Fluctuating demand often leads to overstock and stockout risks, increasing holding costs and potential lost sales. Historical daily demand data were used to construct a probabilistic model, followed by 10,000 simulation iterations to generate the probability distribution of total inventory costs. The cost model consists of holding costs and shortage costs. The simulation results indicate that total cost follows a probabilistic distribution and that an optimal reorder point exists to minimize the expected total cost. Sensitivity analysis confirms the trade-off between holding and shortage costs. The findings demonstrate that Monte Carlo simulation effectively supports adaptive, risk-based, and efficient inventory decision-making for small-scale retail businesses.