RR Score Methodology

A detailed explanation of how RANKNESIA calculates university scores and rankings.

Data Sources

RANKNESIA uses 100% data from OpenAlex — an open research database licensed under CC0 (free to use without restrictions).

Not using: Scimago, Scopus, QS, THE, UI GreenMetric, or other paid/restricted data sources.

Indicators & Weights

1

Research Output

25%

The total number of the university’s scientific publications from OpenAlex (works_count). Measures overall research productivity.

Field OpenAlex: works_count

2

Research Impact

25%

Number of citations divided by the number of publications (cited_by_count / works_count). Measures the impact and influence of research.

Field OpenAlex: cited_by_count / works_count

3

Research Quality

15%

Average citations per publication in the last 2 years (2yr_mean_citedness). Measures the quality of recent research.

Field OpenAlex: summary_stats.2yr_mean_citedness

4

Research Breadth

30%

Number of publications with at least 10 citations (i10_index). Measures how broad the research impact is institutions with many influential papers will excel.

Field OpenAlex: summary_stats.i10_index

5

H-Index

5%

Institutional H-Index from OpenAlex. Measures the consistency of research impact over time.

Field OpenAlex: summary_stats.h_index

Pipeline Normalization

L1
Ratio
Convert raw values into ratios (publications/lecturer, citations/publication, etc.)
L2
Log Transform
Apply log(x+1) to dampen extreme outliers
L3
Min-Max 0–100
Normalize to scale 0–100: (x−min)/(max−min) × 100
L4
Weighted Sum
RR Score = Σ(skor × bobot) − total_penalty_points

Final Formula

# RR Score Formula (v2 — 2026)

RR Score =

(0.25 × Output_norm)

+ (0.25 × Impact_norm)

+ (0.15 × Quality_norm)

+ (0.30 × Breadth_norm)

+ (0.5 × Hindex_norm)

− Total_penalty_points

The minimum score is 0 (cannot be negative). The theoretical maximum score is 100.

Penalty System

Universities may be subject to point deductions if proven to have committed violations of academic ethics. Reports from the public will be verified by the RANKNESIA team before penalties are enforced.

LevelReductionWhen is it used
Light−0.5Minor violations, not fully confirmed
Medium−1Confirmed violations, limited impact
Heavy−3Serious violations, strong evidence available
Very Heavy−5Serious violations, wide impact
DANGER−10Systemic cases / repeated / highly viral

Notes & Limitations

Why do larger institutions tend to perform better?

RANKNESIA measures Research Productivity and Impact in absolute terms. Institutions with high research volume such as the University of Washington or Harvard will excel because this methodology is not normalized by the number of faculty or students — that data is not available in OpenAlex.

Not a replacement for the existing rating agencies

RANKNESIA does not measure academic reputation, the faculty-to-student ratio, or campus internationalization. This ranking is a transparent, open-data-based alternative, not a direct competitor to other ranking agencies.

Data is updated 2x per year

The RANKNESIA rankings reflect OpenAlex data as of the time the pipeline was run (January and July). Changes in rankings between periods reflect changes in institutional research productivity.

Update Schedule (RADAR)

Data ranking is updated twice per year through the RADAR system (Ranking Data Refresh). Each update fetches the latest data from OpenAlex.

RADAR 1
January
2026 RADAR 1
RADAR 2
July
2026 RADAR 2