Strategies to Improve Data Quality Management Using Total Data Quality Management (TDQM) and Data Management Body of Knowledge (DMBOK): A Case Study of M-Passport Application
DOI:
https://doi.org/10.21512/commit.v17i1.8330Keywords:
Data Quality Management, Total Data Quality Management (TDQM), Data Management Body of Knowledge (DMBOK), M-Passport ApplicationAbstract
M-Passport is a mobile application developed for Indonesians to request for passport online. The applicants independently input all required data using this application, so the quality of data entered must be considered to ensure the passport’s validity as an official state document. However, input errors increase the time needed for the interview process and make the data verification procedure inefficient. The research aims to assess the data quality of M-Passport for organizations to take deliberate actions to enhance the data quality. The research applies the Total Data Quality Management (TDQM) method and the Data Management Body of Knowledge (DMBOK). Six data quality dimensions are used. It consists of completeness, validity, accuracy, timeliness, uniqueness, and consistency. The measure phase is carried out on 17 entities in the M-Passport database through a query process in the production environment. Then, the analysis phase observes the problems based on the pre-determined dimensional classification groups. The result indicates that the average values of completeness, validity, accuracy, consistency, timeliness, and uniqueness are 99.20%, 99.41%, 100%, 90.68%, 78.52%, and 99.98%, respectively. According to the findings, timeliness and consistency are the lowest dimensions in fulfilling business rules. It indicates that organizations need to focus more on improving data quality in these dimensions. Then, based on the DMBOK, the research also generates recommendations for resolving technical and operational issues.
Plum Analytics
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