Data Quality Assessment: A Case Study of PT JAS Using TDQM Framework

Wahyu Ari Bowo, Agus Suhanto, Meisuchi Naisuty, Syukron Ma'mun, Achmad Nizar Hidayanto, Ika Chandra Habsari

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

1 Citation (Scopus)

Abstract

The success of a company in increasing profits and managing loss risk is largely determined by data. Good quality data can improve the quality of decision making at the top management level. PT JAS is a financial company that manages risk. Of course to support good risk management needs to be supported by good quality of data sources. The aim of this research is to identify data dimensions, analyze and measure the quality of data. So that, it can be used as a support for the company's strategy in managing risk and understanding the current conditions of data quality. In measuring this data quality, the writer uses a total data quality management (TDQM) framework. TDQM provides a common framework for facilitating understanding in data improv approach through data quality management. The steps taken in measuring data quality are identification of data to be measured, determining the dimensions of data quality used, measurement of data quality, and then analyze the measurement results. From the measurement results, obtained factors that cause data quality problems, for example the pattern of imports of debtor data in large numbers. In addition, there are no policies related to data quality management and from some validation function errors in the system. Therefore, by measuring the quality of data and analyzing the causes, companies can find out in advance the condition of the quality of company data and immediately formulate strategies and steps in order to improve and develop the quality of the data they have, so that data can be a useful and valuable asset.

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

  • case study
  • data dimension
  • data quality
  • data quality assessment
  • TDQM

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