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Selamat Datang di Pelayanan Statistik Terpadu (PST) BPS Kabupaten Minahasa Selatan, Jl Trans Sulawesi Minahasa Selatan, email: bps7105@bps.go.id - Tlp: (0430)22798

Internalization of Statistics Recommendation of BPS-Statistics of Sulawesi Utara Province

August 18, 2021 | Other Activities

Wednesday, August 18th 2021. BPS of North Sulawesi Province held an internalization of statistical recommendations to all Regency/City BPS in North Sulawesi Province. This activity is a follow-up to similar activities that have been organized by BPS to all Provincial BPS throughout Indonesia. This statistical recommendation internalization activity was held to further enrich the knowledge of BPS employees in implementing statistical recommendations for K/L/D/I. The provision of statistical recommendations is a concrete manifestation of the role of BPS in developing sectoral statistics.

The internalization of statistical recommendations from BPS of North Sulawesi Province was attended by 65 participants consisting of 5 participants representing each function at BPS of North Sulawesi Province and 60 participants from BPS Regency/City in North Sulawesi Province. Each district/city is represented by 5 participants representing each function at the Regency/City BPS. The speakers in this activity were statistical functional officials who came from functions at the BPS North Sulawesi Province, namely Munawir Kobis, Enggelin Giacinta Wongkar, Junetha Joce Sahureka, Victor Sirait, Indira Anastasya Lolowang, and Frisda Arisanti Tarigan.

In his remarks during the opening ceremony, the Head of BPS for North Sulawesi Province, Asim Saputra, SST, MEcDev conveyed the importance of statistical recommendations. Statistical recommendations issued by BPS for sectoral survey activities carried out by K/L/D/I are a mandate of legislation. This recommendation is given so that surveys conducted by K/L/D/I can be accounted for academically. District/city BPS is expected to be able to disseminate this statistical recommendation among K/L/D/I in their respective regions so that the quality of sectoral data produced by K/L/D/I increases.

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