Indonesia's Gen Z Majority: Reading the 2025 SUPAS Data Through a Statistical Lens

On May 5, 2026, Indonesia's Central Statistics Agency (BPS) released the results of the 2025 Intercensal Population Survey (SUPAS). The headline figure: Indonesia's population reached 284.67 million, up from 237.64 million in the 2010 census. What drew more attention wasn't the total, though — it was the composition. Gen Z was recorded as the largest generational group at 24.93%, followed closely by Millennials at 24.34%. Combined, these two younger generations account for nearly half of the national population.

BPS Head Amalia Adininggar Widyasanti described the finding as reflecting a dominance of working-age groups in the country's current demographic structure.

But for anyone who works with data, a headline number like this should prompt a follow-up question: where does it come from, and how far can it actually be stretched into a conclusion?

SUPAS Isn't a Census — and That Matters

The first methodological point that's easy to miss: SUPAS is a sample-based survey, not a full census. Unlike the Population Census (SP), which counts the entire population, SUPAS samples households between two census periods to fill the ten-year data gap.

What that means for reading the numbers:

- Every published percentage (24.93% for Gen Z, for instance) is an estimate, not an exact count — carrying a margin of error, even when BPS's press releases don't always publish the confidence interval. - The sampling design (regional stratification, survey weighting) determines how representative this national figure is of province-to-province variation. 24.93% is a nationally weighted average — it doesn't mean every province shares the same generational mix. - Because population is still concentrated in Java (55.65%), the national figure naturally skews toward Java's demographic pattern relative to other regions. ## Reading the Generational Numbers Critically

A few other findings from SUPAS 2025 round out the picture:

- Age structure is shifting. The working-age share (15–64) rose from 66.09% (2010 census) to 68.94% (2025). Meanwhile, the 0–14 age group fell from 28.87% to 23.44%. - Indonesia is entering an aging-population phase. The elderly share rose from 7.59% (2010) to 11.97% (2025) — crossing the 10% threshold that marks a transition toward an aging population. - The dependency ratio sits at 45.05 — meaning every 100 working-age people support roughly 45 non-working-age people. This is the basis of the "demographic dividend" claim: a low dependency ratio opens an economic window of opportunity, but that window narrows as the population ages. - Population growth has slowed to 1.08% annually over the past five years, down from 1.10% previously, tracking a total fertility rate that has eased to 2.13 births per woman. One thing worth flagging: the birth-year ranges used to define each generation (Gen Z, Millennial, etc.) aren't fully standardized — different institutions use slightly different cutoffs. That's not a BPS error; it's a reminder that generational labels are a social construct, not a precise statistical category like a 5-year age bracket. When comparing figures across sources, it's worth checking the cohort definition before putting them side by side.

Why This Matters for Anyone Working With Data

For anyone building models or analysis on national survey data (Susenas, SUPAS, or anything derived from them), this SUPAS 2025 release carries a few practical implications:

• Generational weighting in the sample will shift. Any study using recent household-level data should account for a target population that now skews younger and more urban than a decade ago.
• Watch for ecological fallacy. The national figure of 24.93% can't be directly used to infer the generational makeup of a specific district or city — regional variation (rural vs. urban, Java vs. outside Java) can diverge sharply from the national average.
• A narrowing dependency ratio is relevant for data-driven policy projections — from labor-force planning to designing social-security programs for a growing elderly population.