Abstract:
The Central Statistics Agency (BPS) is a government institution that has the authority to carry out statistical activities in the form of censuses and surveys, to produce statistical data needed by the government, the private sector and the general public, as a reference in planning, monitoring, and evaluation of development results. Therefore, providing quality statistical data is very decisive because it will have an impact on the effectiveness of decision making. This paper aims to develop a framework to determine priority of solutions in overcoming data quality problems using the Analytic Hierarchy Process (AHP). The framework is built by conducting interviews and Focus Group Discussion (FGD) on experts to get the interrelationship between problems and solutions. The model that has been built is then tested in a case study, namely the Central Jakarta Central Bureau of Statistics (BPS). The results of the study indicate that the proposed model can be used to formulate solutions to data problems in BPS.
Machine summary:
Framework for Prioritizing Solutions in Overcoming Data Quality Problems Using Analytic Hierarchy Process (AHP) Imelda Aritonang Doharta MSc Student.
This paper aims to develop a framework to determine priority of solutions in overcoming data quality problems using the Analytic Hierarchy Process (AHP).
Quality data and information is needed for the organization so that the organization can make decisions quickly and correctly, especially due to the increasing amount of data that must be managed by the organization (Gürdür, El-khoury, & Nyberg, 2018; Haegemans, Snoeck, & Lemahieu, 2019).
, 2019; Mendes, Dong, & Sampaio, 2015; Yeganeh, Sadiq, & Sharaf, 2014).
The government needs to provide statistical data as an indicator of development, which is used both by the internal government itself and by the private sector to get an accurate picture of the macro environment, which is useful for business planning (Duvier, Neagu, Oltean-dumbrava, & Dickens, 2018).
Poor decision making could be the serious impact caused by poor data quality of an organization (Keller & Staelin, 1987; Chengalur-Smith, Ballou, & Pazer, 1999; Raghunathan, 1999; Jung, Olfman, Ryan, & Park, 2005; Shankaranarayanan & Cai, 2006; Ge & Helfert, 2008) and finally risks organizational performance (Redman, 1998; Fisher & Kingma, 2001; Eppler & Helfert, 2004; Slone, 2006).
Table 1 below presents the barrier of data quality management from several previous studies (Umar, 1999; English, 1999; Xu, Nord, Brown, & Nord, 2002; Haug and Arlbjorn, 2010).
Framework for Prioritizing Solutions in Overcoming Data Quality Problems Using Analytic Hierarchy Process (AHP).