A Bibliometric Analysis of Undergraduate Theses in Industrial Engineering Undergraduate at Universitas Trisakti: Research Trends and Future Directions
Year: 2025
Type: article
Abstract: Industrial Engineering (IE) is a multidisciplinary field that evolves alongside technological advancements and global challenges. While bibliometric analyses are commonly used to assess journal publications, limited studies focus on the research trends within undergraduate theses, especially in Indonesia. Understanding these trends is essential for aligning academic curricula with emerging research areas. This study analyzes research trends in undergraduate theses at Universitas Trisakti's Industrial Engineering Department between 2021 and 2024. Data were collected from the campus repository and filtered using the keyword “industrial engineering.” A bibliometric analysis was conducted using Microsoft Excel for data processing and Python for computational mapping. K-means clustering was applied to identify active supervisors and research collaborations across laboratories. A total of 350 theses were analyzed, showing a peak in publications in 2021 (130 theses). The Quality Engineering Laboratory emerged as the most active contributor, with standard methodologies including FMEA, Six Sigma, Simulation, and Sustainable Practices. Key supervisors such as Triwulandari, Didien S, and Wawan K significantly shaped research directions. The study recommends integrating emerging technologies such as AI, machine learning, and Industry 4.0 to enhance future research relevance and industrial applications.
Source: JURNAL TEKNIK INDUSTRI
Institution: Universitas Trisakti
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410018185