This study investigates the technical efficiency of Indonesian public service universities (PTN-BLU) using Data Envelopment Analysis (DEA), focusing on variations across time and model specifications. The research aims to assess whether institutions that were efficient between 2017 and 2019 maintained their performance through 2023, and how different combinations of input-output variables affect efficiency outcomes. Two DEA models were applied using R programming and were compared with previous results from Sulaeman and Adzillah. The analysis included data on academic, financial, and institutional outputs, covering 48 PTN-BLU. Findings show that only a limited number of universities sustained efficiency over time, suggesting institutional changes or policy impacts. A comparison of the two models revealed substantial differences in efficient unit rankings, demonstrating the sensitivity of DEA results to variable selection. Additionally, slack analysis indicated that improvements are needed in both inputs and outputs for most inefficient institutions. The study concludes that an integrative DEA model offers a more comprehensive understanding of university performance, and recommends further research using standardized data to support long-term efficiency evaluation in higher education.
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