Enumerators’ Characteristics and Data Quality in Susenas 2025: A Logistic Regression Study

DOI

10.2991/978-94-6239-709-5_89How to use a DOI?

Keywords

Biographic-characteristic; Data-Quality; Susenas-Enumerator; Logistic-Regression; Statistic-Indonesia

Abstract

This study employs data from the 2025 National Socio-economic Survey (Susenas) conducted in South Sulawesi Province, Indonesia. This research examines the causal effect of enumerators’ biographical characteristics on data quality. A quantitative approach was adopted, with binary logistic regression applied to evaluate the influence of five key enumerator characteristics age, gender, educational attainment, prior Susenas experience, and primary occupation on data quality outcomes. The results indicate that enumerator biographical attributes collectively exert a statistically significant effect on the likelihood of producing high-quality survey data. At the individual level, gender, prior Susenas experience, and occupation demonstrated statistically significant associations with improved data quality; notably, homemakers and self-employed individuals contributed most prominently to this effect. Female enumerators demonstrated a higher probability of generating accurate responses compared to their male counterparts. In line with these findings, prior Susenas experience and occupational background were positively correlated with data reliability. These results underscore the relevance of personal attributes in shaping field performance and suggest that recruitment strategies should incorporate both experiential and occupational considerations. Enhancing enumerator training is further recommended to ensure the consistency and integrity of future Susenas data collection efforts.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Iin Jumsinah
AU  - Mahlia Muis
PY  - 2026
DA  - 2026/06/20
TI  - Enumerators’ Characteristics and Data Quality in Susenas 2025: A Logistic Regression Study
BT  - Proceedings of the 10th International Conference on Accounting, Management, and Economics (10th ICAME 2025)
PB  - Atlantis Press
SP  - 1290
EP  - 1308
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-709-5_89
DO  - 10.2991/978-94-6239-709-5_89
ID  - Jumsinah2026
ER  -