BPS-Statistics Ternate Municipality Conducts Training for 2026 Economic Census (SE2026) Officers

Ternate, June 10 2026 – BPS-Statistics Ternate Municipality has conducted training for the 2026 Economic Census (SE2026) officers as part of the preparation for field data collection activities, which will take place from June 15 to August 31, 2026. The training was organized in two batches, June 3–5, 2026 and June 8–10, 2026, at Grand Majang Hotel and Jati Hotel, Ternate Municipality.

The activity was attended by 151 participants consisting of 128 Door-to-Door Census Field Officers, 20 Door-to-Door Census Field Supervisors, 2 Large Enterprise (UB) Census Field Officers, and 1 UB Census Field Supervisor. In addition, the training was also attended by sit-in participants from the Resort Police of Ternate who are expected to support the 2026 Economic Census in Ternate Municipality.

In his remarks, the Chief of BPS-Statistics Ternate Municipality, Ahmad Abdurrahman, stated that the 2026 Economic Census is a strategic activity conducted once every ten years to obtain a comprehensive overview of the structure and characteristics of economic activities in Indonesia. The census results will serve as an important basis for formulating economic development policies and planning at both the national and regional levels.

Through this training, BPS-Statistics Ternate Municipality expects all officers to have optimal readiness before going into the field so that 2026 Economic Census can produce high-quality data. The resulting data will become an important basis for formulating more targeted economic development policies to support the realization of a resilient and sustainable economy.

As a symbol of readiness for the implementation of the activity, a ceremonial vest-wearing session for the 2026 Economic Census Officers was conducted symbolically for representatives of the participants. This momentum also marked the beginning of a shared commitment to the success of SE2026 in producing accurate, high-quality, and reliable economic data.