Collaborative Visit from BPN and KP2KP Mamasa

[Mamasa, August 22, 2024] – The Central Statistics Agency (BPS) of Mamasa Regency received a visit from the Head of the Land Office/National Land Agency (BPN) of Mamasa Regency and the Head of the Tax Service, Counseling, and Consultation Office (KP2KP) of Mamasa Regency on Thursday (22/8). This meeting aimed to strengthen inter-institutional synergy to improve the effectiveness of planning and evaluating development in the Mamasa region.

During the meeting, the three institutions agreed to enhance cooperation in sharing data and information held by each party. This step is considered strategic because the utilization of integrated data will provide a stronger foundation for decision-making, planning, and evaluating development in Mamasa Regency.

The Head of BPS Mamasa Regency, Aan Setyawan, stated that this collaboration is very important in creating policies based on accurate and comprehensive data. “With the synergy between BPS, BPN, and KP2KP, we can combine various data sources that will provide a more holistic view of regional development needs,” he said.

Meanwhile, the Head of the Land Office/BPN of Mamasa Regency, Muhammad Ridwan, added that the land data they have can be used to map the region and land development potential. “This data can later be integrated with social and economic data from BPS as well as tax information from KP2KP, so that development planning will be more targeted,” he explained.

The Head of KP2KP Mamasa Regency, Yudha Kris Okta Rianto, also expressed his view that this synergy can help optimize local tax revenue. “With more integrated data, we can map potential tax revenue and develop more effective strategies in regional financial management,” he said.

The meeting concluded with an agreement to form a cross-agency technical team responsible for developing data sharing and utilization mechanisms. It is hoped that this collaboration can have a positive impact on the development of Mamasa Regency, with more efficient, effective, and data-driven policies.