Measurement of Export Data Quality Using Task-Based Data Quality (TBDQ): Case Study of the Directorate General of Customs and Excise

Abstract

The Indonesian Directorate General of Customs and Excise (DGCE), as the regulator of export policies in Indonesia, is required to have good quality export data. However, in its management, export data were reported to have persistent problems based on reports of export evaluations and the results of data cleansing with relevant stakeholders. These problems should be addressed immediately because export data is vital for Indonesia, therefore it is necessary to measure the quality of export data at the Indonesian DGCE. One of the benefits of measuring export data is to investigate existing data problems, hence it is easier to set a number of improvements. This study uses the Task-Based Data Quality (TBDQ) framework because it matches the characteristics of the export information system. The dimensions used in this study are Completeness, Accuracy, Timeliness, and Consistency determined from interviews with experts. The results showed that the quality of export data is not yet optimal with the highest anomaly percentage of 1.4494%. Improvements of the anomalous data are made based on the Improving Task by the weighting calculation, that has been done using the Analytic Hierarchy Process (AHP) so that the problems of data accuracy and differences in the results of data cleansing can be eliminated.