AGRICULTURAL ECONOMIC SURVEY AGENTS TRAINING (SEP) 2024

The Tegal District Central Bureau of Statistics (BPS) is conducting the Agricultural Economic Survey (SEP) agents training for 2024 with a combination of online and offline methods over 4 days. The online training took place on May 27-28, 2024 through a Zoom meeting. Meanwhile, the offline training was held at the Grand Dian Hotel, Slawi on May 29-30, 2024.

The SEP training instructor is Winda Dwi Janingrum, SST, who received the 2nd best Regional Instructor (Inda) predicate in BPS Central Java Province. There are a total of 23 participants in the training, consisting of 17 field data collection agents and 6 field inspection agents. The field data collection agents are statistical partners recruited in November 2023, while the field inspection agents are organic members of the Tegal District Central Bureau of Statistics.

The aim of this training is to equip agents with the concept, definition, and data collection procedures according to the established Standard Operating Procedures (SOP) so that the agents are expected to meet the predetermined competencies.

During the training, agents were provided with materials related to agricultural economic surveys, data collection techniques, document filling procedures, and data collection methods. Agents also underwent direct interview training with peers through role-playing scenarios with two respondents.

With the implementation of the SEP 2024 Training, the Tegal District Central Bureau of Statistics hopes to improve the accuracy and credibility of the agricultural economic survey data produced. Accurate and high-quality data is crucial for proper planning and decision-making in the agricultural sector.

This training is one of the efforts by the Tegal District Central Bureau of Statistics to support sustainable agricultural development based on data. Moving forward, the Tegal District Central Bureau of Statistics will continue to enhance the capacity of human resources in the field of statistics to meet the increasingly complex and dynamic data needs.(Myla)