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Abstract
Background. Higher education strategic plans (Renstra) tie institutional visions to operational targets. Yet document length, format, and mission differ across institutions. That makes it hard to read lexical frequencies as discrete governance typologies.
Objective. To measure lexical attention to four strategic orientations (internationalization, research downstreaming, inclusivity, and digital transformation). It also tests whether Indonesian higher education institutions form stable, well-separated clusters.
Methods. This exploratory computational text-as-data analysis covered 51 official Renstra documents for 2025 (39 public [PTN] and 12 private [PTS] institutions in six regions) and yielded 13,275 non-overlapping 80-token windows (923,823 alphabetic words). A pre-specified 24-concept dictionary was combined with Normalized Pointwise Mutual Information (NPMI) co-occurrence networks, Ward clustering, 1,000 marginal feature-permutation null models, 1,000 subsampling runs, and 14 sensitivity analyses.
Results. Equal-weight institutional mean positive window proportions were 28.0% (95% bootstrap CI: 25.4–30.8%) for internationalization, 12.1% (10.8–13.5%) for digital transformation, 11.5% (10.0–13.1%) for research downstreaming, and 6.8% (5.8–8.0%) for inclusivity. The co-occurrence network had 24 nodes, 138 edges, and four communities. The best four-cluster partition (n = 14, 13, 14, and 10; silhouette = 0.166) did not beat the marginal permutation null (median = 0.201; empirical p = 0.961). Subsampling gave a median Adjusted Rand Index (ARI) of 0.389, selected k = 4 in 50.8% of runs, and left 58.6% of institution pairs ambiguous. Sensitivity ARIs ranged from 0.091 to 0.699.
Conclusion. Across 51 strategic plans, lexical attention to the four orientations varies considerably. The data do not justify discrete institutional typologies. Continuous profile reporting is preferable.
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