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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Rismansyah, Ari
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Computer Science & IT

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A Hybrid Method for Standardising Civil Registration and Vital Statistics (CRVS) Location Data Sandyawan, Ignatius; Rimawati, Yeni; Rismansyah, Ari
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.618

Abstract

 Civil Registration and Vital Statistics (CRVS) systems in archipelagic contexts likeIndonesia face persistent challenges in location data standardisation due to free-text entries thatvary in spelling, formatting, and granularity. This study introduces a multi-stage hybridframework that systematically converts these unstructured entries into official administrativecodes using deterministic matching, fuzzy probabilistic matching, and geocoding. This studyprocessed 841,126 birth and death records using Python (Pandas, RapidFuzz, Geopy).Cumulatively, all stages achieved a combined match rate of 85.44% for births and 67.12% fordeaths. The layered pipeline ensured speed, precision, and coverage for real-world CRVS data.The findings demonstrate enhanced geographic precision in vital statistics, enabling morereliable public health and demographic applications. Future improvements may includetransformer-based embeddings, active learning for ambiguous records, and uncertainty-awaregeocoding techniques. This framework establishes a scalable, robust pathway for elevating thegranularity and reliability of geolocated vital event data.
Co-Authors Rimawati, Yeni Sandyawan, Ignatius