Data Quality Management Strategy to Improve the Quality of Worker's Wage and Income Data: A Case Study in BPS-Statistics Indonesia, 2018

Sinta Denovi Rahmawati, Yova Ruldeviyani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data quality was a problem for professionals and academics in their research. The issues of poor data quality will harm the organization's business. Based on the quality target of social statistics in the strategic plan of BPS-Statistics Indonesia in 2015-2019 and worker's wage and income data from the Survey of Data Requirement (SKD) in 2017, there is 59 percent gap between expectations and realization of data quality satisfaction. Therefore, the assessment of the data quality management maturity model is important because it will be the basis for making recommendations to improve data quality. The framework used in this study is the data quality framework by David Loshin and DQM DMBOK. Overall, the average of data quality maturity level is still at level 3 (defined). From the results of the data quality maturity level, a list of characteristic gaps that have not been implemented is obtained. The results of the gap mapping get several DQM activities based on DMBOK. This activity is described as several strategy recommendations for improving the quality of worker's wage and income data.

Original languageEnglish
Title of host publicationProceedings of 2019 4th International Conference on Informatics and Computing, ICIC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728122076
DOIs
Publication statusPublished - Oct 2019
Event4th International Conference on Informatics and Computing, ICIC 2019 - Semarang, Indonesia
Duration: 23 Oct 201924 Oct 2019

Publication series

NameProceedings of 2019 4th International Conference on Informatics and Computing, ICIC 2019

Conference

Conference4th International Conference on Informatics and Computing, ICIC 2019
Country/TerritoryIndonesia
CitySemarang
Period23/10/1924/10/19

Keywords

  • Data Quality Management
  • DMBOK
  • DQM
  • Loshin's framework

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