IPB University Professor Reveals the Role of SAE and Big Data in the Preparation of Official State Statistics
Professor of the School of Data Science, Mathematics and Informatics of IPB University, Prof Anang Kurnia explained the contribution of statistics and data science in the preparation of official state statistics in Indonesia.
“With statistics and data science, we try to get meaningful insights from a set of data. In the end, we can use it to make decisions and develop follow-up recommendations,” he explained in the Pre-Scientific Oration Press Conference (23/1) via Zoom Meeting.
On the other hand, continued Prof Anang, in line with the development of regional autonomy, one of the main challenges in official state statistics is to estimate or measure accurate sustainable development indicators for areas smaller than the autonomous region, such as statistics for the sub-district level or even the village level.
“Small area estimation (SAE) is a method or algorithm of statistics and data science that can be used with the aim of obtaining reliable predictions or estimators of parameters of concern for the subdomain level in the form of smaller administrative areas,” he said.
In his research, Prof Anang and his team found that big data and SAE have the potential to revolutionize the way parameters of concern are estimated, especially in compiling official state statistics.
“SAE is able to produce statistical data that has good accuracy for the subdomains of concern. Meanwhile, big data has great potential as a source of accompanying variables in the context of SAE, a substitute for surveys, even as a basis for developing new SAE models,” he explained.
From his research, it can be seen that statistics and data science are important for finding solutions to problems faced by government and industry, as well as increasing the real contribution to the innovations developed.
“Institutionally, we consider it necessary to establish a Collaborative Research and Innovation Center (CRIC) of Data Science. This CRIC model will produce statistics and data science through academic collaboration (universities), government, and industry,” he said.
Prof Anang added, to ensure the quality of big data used, the most important thing is that the people who manage the data must have honesty followed by skills to manage data.
“We always emphasize that a statistician or data scientist must work with experienced experts. This cooperation will be able to maintain the quality of reliability and validity of the data,” said Prof Anang. (Lp) (IAAS/RUM)
