Data Governance Maturity Level at the National Archives of the Republic of Indonesia

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Sari Agustin Wulandari


The National Archives of the Republic of Indonesia (ANRI) as an institution given mandate to carry out state duty in the field of archives has vision as a pillar of good governance and nation’s collective memory. To implement it, the study of the grand design of the archival system arranged. That is very related to the data governance implementation. Therefore, ANRI needs to know the maturity level of the data governance function which had been held. The assessment was done by referring to the Stanford Data Governance Model. The result showed that data governance is still at an initial level. The foundational aspects are on an average of 1,2 which contains awareness, formalization, and metadata. While on project aspects are on average of 1,5 consisting of stewardship, data quality, and master data. In total, ANRI is at the level of 1,35. ANRI needs to make improvements for data management planning activities referring to Data Management Body of Knowledge (DMBOK) with a focus on people, policies, and capabilities dimensions in all aspects. This research is expected to be helpful for ANRI to make improvements corresponding to the recommendations thus ANRI could implement national data archival properly.

Article Details

Author Biography

Sari Agustin Wulandari, Universitas Indonesia

Pusdatin ANRI


Al-ruithe, M., & Benkhelifa, E. (2018). Determining the enabling factors for implementing cloud data governance in the Saudi public sector by structural equation modelling. Future Generation Computer Systems.

ANRI. (2009). Undang-Undang No. 43 Tahun 2009 tentang Kearsipan. Retrieved from

ANRI. (2014). Peraturan Kepala Arsip Nasional Republik Indonesia No. 14 Tahun 2014 tentang Organisasi dan Tata Kerja Arsip Nasional Republik Indonesia. Retrieved from

ANRI. (2015). Peraturan Kepala Arsip Nasional Republik Indonesia No. 40 Tahun 2015 tentang Rencana Strategis Arsip Nasional Republik Indonesia Tahun 2015 - 2019.

Data Governance at Stanford : The Stanford DG Maturity Model. (2011).

Data Governance Maturity Model. (2011). Office of Management and Enterprise Services. Retrieved from

Helvoirt, S. van, & Weigand, H. (2015). Operationalizing Data Governance via Multi-level Metadata Management. IFIP International Federation for Information Processing, 9373, 160–172.

Mosley, M., Brackett, M., Earley, S., & Henderson, D. (2009). The DAMA Guide to The Data Management Body of Knowledge ( DAMA-DMBOK Guide ) First Edition.

Permana, R. I., & Suroso, J. S. (2018). Data Governance Maturity Assessment at PT . XYZ . Case Study : Data Management Division. 2018 International Conference on Information Management and Technology (ICIMTech), (September), 15–20.

Proenca, D., & Borbinha, J. (2018). Maturity Models for Data and Information Management, 2(Cmmi), 81–93.

Riggins, F. J., & Klamm, B. K. (2017). Data governance case at KrauseMcMahon LLP in an era of self-service BI and Big Data. Journal of Accounting Education, 38, 23–36.

Saputra, D. A., Handika, D., & Ruldeviyani, Y. (2018). Data Governance Maturity Model ( DGM2 ) Assessment in Organization Transformation of Digital Telecommunication Company : Case Study of PT Telekomunikasi Indonesia, (1).

Wang, C. S., Lin, S. L., Chou, T. H., & Li, B. Y. (2019). An integrated data analytics process to optimize data governance of non-profit organization. Computers in Human Behavior, 101, 495–505.