6–9 Jul 2026
Europe/Warsaw timezone

One Rating, Multiple Services. Solving the 100-Service Dilemma: Automated Attribution for Multi-Service Public Satisfaction Surveys

8 Jul 2026, 14:00
20m
Lightning Talk (5 minutes) Virtual Presentation Room

Speaker

Abdul Aziz Nurussadad (Badan Informasi Geospasial)

Description

Scaling public satisfaction surveys presents a significant challenge for government hubs managing hundreds of distinct services. National regulations of Indonesia (Minister of Administrative and Bureaucratic Reform Regulation 14/2017) mandate measuring nine specific quality components—including staff behavior, requirements, and facilities—for every service provided. However, requiring citizens to repeat identical ratings for each individual service they receive in a single visit leads to severe respondent fatigue and compromised data quality.

This case study demonstrates a "One Rating, Multiple Services" strategy powered by a robust R-based pipeline. We implemented a streamlined data collection workflow using Google Forms, where respondents select all services received (stored as semicolon-separated strings, e.g., "Service A; Service B; Service E") and provide a single set of ratings based on their holistic experience.

Using the {tidyverse} ecosystem—specifically the separate_longer_delim() function from {tidyr}—we developed a "Disaggregate-and-Attribute" pipeline. This workflow automates the duplication of perception scores across specific service IDs, enabling the calculation of individual satisfaction indices for hundreds of services from a manageable volume of raw survey entries. This presentation highlights how R serves as a critical tool for bridging rigid bureaucratic mandates with efficient, human-centric data collection strategies in the public sector.

If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.

No AI tools/services were used.

Keywords: Please list up to 5 keywords to help us find the right session for your contribution. Public Sector, Data Disaggregation, Survey Methodology, Indeks Kepuasan Masyarakat (IKM), Respondent Fatigue
Virtual Option This submission is for pre-recorded virtual presentation only
Video Recording Video sharing is fine
The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. Confirm
Interested in serving as reviewer? abdul.aziz@big.go.id

Authors

Abdul Aziz Nurussadad (Badan Informasi Geospasial) Mrs Akbar Rizki (IPB University)

Presentation materials

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