The Importance of Maintaining the Quality of Susenas Data

From these two 30-45 pages long documents, we are sure to bring dozens or even hundreds of development programs. Both at the central and regional levels (provinces). The National Socio-Economic Survey (Susenas) contains a variety of detailed data related to development.
For example: illiterate population data until population data with sanitation access is not feasible to get the percentage.

Our task (BPS-Statistics of Indonesia) maintains and guarantees the quality of its data. Control management needs to be done from the planning stage, field data collection, field surveillance control, processing control until the final evaluation stage before the data is declared final.
No way, in the age of information and communication now, people are increasingly literate about the importance of data. Data is increasingly needed by in all aspects of society, from government to academia. Centralized reporting on the Central Bureau of Statistics by the President over time has further strengthened the central role of BPS.

Why is it necessary and should be done data quality control management?
In statistics, nonsampling error is known. Unlike the sampling error, nonsampling error can not be measured and calculated what value or error rate caused.

Nonsampling error is very noticeable in the final evaluation phase of data quality.
One effort to minimize (at least prevent) the occurrence of nonsampling error is to perform quality control data, from the planning stage until the final evaluation of data. Example: weak field supervision will open the gap of error, the solution is tightening supervision.

(Collecting) data is expensive, but more expensive to build without data.

Build Indonesia with data.
Diamond in = diamond out