Data Quality Management Strategy To Improve Remote Sensing Data Quality: A Case Study On National Remote Sensing Data Bank

Agnes Sondita Payani, Alia Mutia Mayanda, Adenia Adiresta, Yova Ruldeviyani

Abstract


National Remote Sensing Data Bank (Bank Data Penginderaan Jauh Nasional; BDPJN) is the operational implementer in the field of remote sensing to meet the needs of national data on remote sensing images. Remote sensing images are essential in the Indonesian government for various needs, such as in regional (spatial planning, city boundaries), disaster (forest fires, floods, landslides, earthquakes, volcanic eruptions), plantation, natural resources, and environment sectors. Quality management of BDPJN’s satellite images becomes challenging due to the increasing number of products owned and users annually. For this reason, a data quality management strategy is needed to guarantee and improve the quality of BDPJN data. To develop such a strategy, an assessment of the maturity of BDPJN’s data quality man- agement was conducted from the aspect of data processing by implementing Loshin’s Data Quality Management Maturity Model (DQM3) to find out the characteristics that were lacking. The results were then mapped based on Data Quality Management (DQM) activities in DAMA-DMBOK as a recommendation for data quality management strategies. This study applies quantitative research where data collection was done by distributing questionnaires to 24 respondents who are data stewards of medium, high, and very high-resolution mosaic images. Based on the assessment, BDPJN is in the maturity level of Defined to Managed. The recommendations are 21 DQM activities that can be carried out to improve BDPJN data quality.

Keywords


BDPJN; Data Management; Data Quality Management Maturity Model; Loshin

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References


Pemerintah Indonesia, Undang-Undang Republik Indonesia Nomor 21 Tahun 2013 Tentang Keantariksaan. LN.2013/No. 133, TLN No. 5435, LL SETNEG: 44 HLM; 2013.

Payani AS, Yudha GD, Wahyuningsih SD, Kannia N, Kusapy DS, Simanjuntak D, et al. Uji Keberhasilan Implementasi Master Plan Teknologi Informasi dan Manajemen BDPJN Menggunakan Metode DeLone dan McLean. Jurnal Edukasi dan Penelitian Informatika 2020;6(2):258–266. https://jurnal.untan.ac.id/index.php/jepin/article/view/37757.

Brahmantara RP, Hutapea DY, Ruldeviyani Y. Evaluation on Data Operations Management using CMMI and DMBOK: BDPJN Case Study. In: Proceedings of The 9th International Conference on Cyber and IT Service Management Bemgkulu, Indonesia: IEEE; 2021. p. 69–75. https://ieeexplore.ieee.org/document/9588888.

Al-Salim W, Darwish ASK, Farrell P. Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports. Renewable Energy and Environmental Sustainability 2022;7(17):1–12. https://ui.adsabs.harvard.edu/abs/2022REES....7...17A/abstract.

Bowo WA, Suhanto A, Naisuty M, Ma’mun S, Hidayanto AN, Habsari IC. Data Quality Assessment: A Case Study of PT JAS Using TDQM Framework. In: Proceedings of The 4th International Conference on Informatics and Computing Semarang, Indonesia; 2019. p. 1–6. https://ieeexplore.ieee.org/abstract/document/8985896.

Cichy C, Rass S. An overview of data quality frameworks. IEEE Access 2019;7:24634–24648. https://ieeexplore.ieee.org/ document/8642813.

Izmaya H, Purnamasari D. Pengukuran Indeks Kepuasan Masyarakat Terhadap Pelayanan Dan Kualitas Data Penginderaan Jauh. Jurnal Informatika: Jurnal Pengembangan IT 2021;6(2):93–98. http://ejournal.poltektegal.ac.id/index.php/informatika/article/view/497/1519.

Loshin D. The Practitioner’s Guide to Data Quality Improvement. Elsevier Inc.; 2011. http://www.sciencedirect.com/science/article/pii/B9780123737175000191.

Sabtiana R, Yudhoatmojo SB, Hidayanto AN. Data Quality Management Maturity Model: A Case Study in BPS-Statistics of Kaur Regency, Bengkulu Province, 2017. In: Proceedings of The 6th International Conference on Cyber and IT Service Management Parapat, Indonesia: IEEE; 2018. p. 1–4. https://ieeexplore.ieee.org/abstract/document/8674323.

Wibisono SB, Hidayanto AN, Nugroho WS. Data Quality Management Maturity Measurement of Government-Owned Property Transaction in BMKG. CommIT (Communication and Information Technology) Journal 2018;12(2):59. https://journal.binus.ac.id/index.php/commit/article/view/4470.

Wilantika N, Wibowo WC. Data Quality Management in Educational Data. Jurnal Sistem Informasi 2019;15(2):52–67. https://jsi.cs.ui.ac.id/index.php/jsi/article/view/848.

Henderson D, editor. DMBOK - Data Management Body of Knowledge 2nd Edition. New Jersey, USA: Technics Publication; 2017.

Putri DT, Ruldeviyani Y. Data Quality Assessment for Suspicious Report Using Loshin’S Framework and Dmbok : A Case Study of Financial Transaction Analysis. Jurnal Penelitian Teknologi Informasi dan Komunikasi 2021;12(1):17–26.

Rahmawati SD, Ruldeviyani Y. Data Quality Management Strategy to Improve the Quality of Worker’s Wage and Income Data: A Case Study in BPS-Statistics Indonesia, 2018. In: Proceedings of The 4th International Conference on Informatics and Computing Semarang, Indonesia: IEEE; 2019. p. 1–6. https://ieeexplore.ieee.org/document/8985803.

Indriany HS, Hidayanto AN,Wantania LJ, Santoso B, PutriWU, PinuriW. Data Quality Management Maturity: Case Study National Narcotics Board. In: Proceedings of The 10th IEEE International Conference on Communication, Networks and Satellite Purwokerto, Indonesia: IEEE; 2021. p. 206–212. https://ieeexplore.ieee.org/document/9530824.

Pratiwi M, Ruldeviyani Y. Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ. In: Proceedings of The 4th International Conference on Software Engineering and Information Management Yokohama, Japan: Association for Computing Machinery; 2021. p. 99–105. https://dl.acm.org/doi/10.1145/3451471.3451488.

Agung Budi Prasetyo, Muhamad Irfan Darmawan RM. Analisis Dan Perancangan Tata Kelola Data Sistem Pemerintahan Berbasis Elektronik Domain Data Quality Management Pada DAMA DMBOK v2. Journal eProceedings of Engineering 2019;6(2):7775–7786. https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/10880.

Wibowo NS, Utami E, Fatta HA. Perancangan Struktur Tata Kelola Data di Pemerintah Daerah Menggunakan Framework Data Management Body Of Knowledge. Journal of Computer, Information System & Technology Management 2021;4(1):45–52. http://e-journal.unipma.ac.id/index.php/RESEARCH/article/view/7049/0.

Rianto, Shofa RN, Yusuf E. Implementasi Kualitas Data dalam Peran Tata Kelola Data. Jurnal Siliwangi 2020;6(1):44–52. https://jurnal.unsil.ac.id/index.php/jssainstek/article/view/2508.

Widjaya W, Sutedja I, Hartono AW. Key aspects of data management framework for early adopter: A systematic literature review. ICIC Express Letters 2019;13(9):761–771.

Cai L, Zhu Y. The challenges of data quality and data quality assessment in the big data era. Data Science Journal 2015;14:1–10. https://datascience.codata.org/articles/10.5334/dsj-2015-002/.

BSN, Badan Informasi Geospasial, Informasi Geografi/Geomatika, editor, SNI ISO 19157:2015 Informasi geografis - Kualitas data. BSN; 2015.

Bitterer A, Gartner’ s Data Quality Maturity Model. Gartner; 2007. https://www.gartner.com/en/documents/500906.

Baskarada S. IQM-CMM: Information Quality Management Capability Maturity Model. Wiesbaden GmbH, Wiesbaden: Vieweg+Teubner Verlag Wiesbaden; 2008. https://link.springer.com/book/10.1007/978-3-8348-9634-6.

Suhardi, Gunawan IGNAR, Dewi AY. Total Information Quality Management-Capability Maturity Model (TIQM-CMM): An information quality management maturity model. In: Proceedings of 2014 International Conference on Data and Software Engineering Bandung, Indonesia; 2014. p. 1–6. https://ieeexplore.ieee.org/abstract/document/7062675.

Fidler M, Lavbic D. Improving information quality of Wikipedia articles with cooperative principle. Online Information Review 2017;41(6):797–811. https://www.emerald.com/insight/content/doi/10.1108/OIR-01-2016-0003/full/html.

Schäffer T, Leyh C, Bley K, Schimmele M. Towards an open ecosystem for maturity models in the digital era: The example of the data quality management perspective. In: Proceedings of The Americas Conference on Information Systems 2018: Digital Disruption; 2018. p. 1–10.

MMiftahul Akbar. Evaluasi TingkatKematangan E-government Dan Partisipasi Masyarakat dalam Pelayanan Publik (Studi Kasus Kabupaten Sukoharjo). PhD thesis, Universitas Islam Indonesia; 2020.

Shrayner YS, Vladimir YV. Maturity models of quality management system in high-tech industry: A systematic literature review. In: Proceedings of The 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019 Saint Petersburg and Moscow, Russia: IEEE; 2019. p. 1478–1484. https://ieeexplore.ieee.org/document/8656993.

Gunawan F, Ruldeviyani Y. Improving Data Quality in Crowdsourced Data for Indonesian Election Monitor: A Case Study in KawalPilpres. Journal of Physics: Conference Series 2020;1566(1):0–6. https://iopscience.iop.org/article/10.1088/1742-6596/1566/1/012095.

Setiadi Y, Hidayanto AN, Rachmawati F, Yohannes AYL. Data Quality Management Maturity Model: A Case Study in Higher Education’s Human Resource Department. In: Proceedings of The 7th International Conference on Computing, Engineering and Design Sukabumi, Indonesia: IEEE; 2021. p. 1–6. https://ieeexplore.ieee.org/document/9664881.




DOI: http://dx.doi.org/10.12962/j20882033.v33i3.14198

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