Jakarta - "Since regional autonomy was implemented, there has been a change of government from centralization to decentralization which gives authority to local governments to make development plans independently. This change certainly requires the support of BPS data. At present the BPS design data is still limited to national and provincial levels. While for the regency / city level, there are still a few, "said Margo Yuwono, Deputy of BPS Social Statistics in front of 75 participants of the first phase of Small Area Estimation (SAE) training from central BPS, IPB, and representatives of the National SDGs Secretariat at Grand Mercure Kemayoran Hotel , (6/19).
The number of SDGs indicators expected by the government is available at BPS as many as 117 indicators at the national level, 105 indicators at the provincial level, and 67 indicators at the district / city level. Currently only 83 and 67 indicators are available at national and provincial levels. For district / city level, it is not yet available. "With SAE, it is expected that the gap between national and district / city levels can be eliminated, thereby facilitating local governments to make policies," Margo added.
On the same occasion, Prof. Dr. Khairil Anwar Notodiputro, Dean of the IPB Postgraduate explained, "I remember, based on its history, SAE was first spoken by the late Sutjipto Wirosardjono in the 2000s. Pak Tjip said that now the era of reform, which must be observed is the change in a centralized system to decentralization. The ruling is no longer the center, but the region. The impact is that BPS must change its thinking. You can no longer think centrally, in terms of data, for example, it can no longer be as if the data is in all centers, BPS must have thought about SAE. "
The needs of regional heads for data at the micro level are increasingly high. If the sample is small, then SAE will produce effective and efficient statistics. SAE utilizes other information such as information from other neighboring areas that are closely correlated or the results of repeated surveys. The benefits, the costs incurred for data collection are more efficient, but produce statistics with sufficient accuracy.
