Collaborative governance in efforts to alleviate poverty through the Social Security Number (SSN) program in Samarinda - Fahriza, Syahnaz; Nurrahman, Muhammad Arif (Priviet Social Sciences Journal, 2026)
Poverty remains a complex social issue that requires integrated handling by various parties. In this context, the Samarinda City Government developed the Social Security Number (SSN) Program as a regional policy innovation to strengthen social protection and expand access to assistance for underprivileged communities. This study aims to analyze the implementation of collaborative governance in the execution of the Social Security Number (SSN) Program in Samarinda City as an effort to alleviate poverty. The research method used is descriptive qualitative with data collection techniques through observation, interviews, and documentation. The results of the study indicate that collaborative governance in the implementation of the Social Security Number (SSN) program has run quite well, marked by a clear division of roles among actors, ongoing coordination, and community involvement in the implementation process. However, the collaborative governance process in the implementation of this program is still functionally administrative, where the planning of collaborative actions and decision-making is still dominated by the government sector, while other sectors play a role by waiting for established instructions and directions. The implementation of the Social Security Number (SSN) Program involves various cross-sector actors, such as the Samarinda City Communication and Information Office, the Samarinda City Social and Community Empowerment Office, Bank Kaltimtara, Perumda Varia Niaga, Districts, Sub-districts, Neighborhood Leaders (RT), E-Warung, and the community. In its implementation, the Social Security Number (SSN) program contributes to reducing poverty through the provision of non-cash food assistance, which helps alleviate the financial burden of poor communities. Nevertheless, the implementation of the program still faces several challenges, such as data dynamics and inaccuracies, technical constraints in using EDC machines, limited public understanding, and the establishment of SSN data as a reference data that is still not uniform.