COLLABORATIVE GOVERNANCE HANDLING PUBLIC COMPLAINTS INDICATIONS OF CORRUPTION IN CENTRAL JAVA-INDONESIA

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Dhoni Widianto, Pujiono, Retno Sunu Astuti, Wijayanto

Abstract

In the context of handling public complaints indicating corruption, collaborative governance between APIP and APH is one of the strategies needed by the government so that the handling of corruption cases is more comprehensive to find out whether the issue is an administrative error or there are indications of elements of unlawful acts. The purpose of the study was to explore the implementation and inhibiting factors of APIP and APH collaborative governance in the context of handling public complaints with indications of corruption in Central Java Province, the collaboration theory of Ansell and Gash (2008), and to analyze the inhibiting factors with the Government of Canada theory (MacDonald, 2008). This research method is the es descriptive qualitative method. The research locus was conducted in Central Java Province. Determination of informants with purposive sample data sources was obtained from APIP and APH sources in Central Java Province. Data analysis was carried outages of data reduction, data presentation, and draw concluding results of the study found that although there were collaboration results, the implementation did not go through a collaborative process such as no face-to-face dialogue (joint forum) with stakeholders for collective decision making, commitment to the process and mutual trust were not optimal, and lack of shared understanding and no role. Facilitative leadership in the collaborative process. It was also found that ten inhibiting factors for collaboration can be categorized into 2 (two) aspects, namely aspects of the Organizational Environment (cultural, institutional, political, regulatory, and economic interests) and Aspects of the Collaborative Process (commitment, trust, coordination, communication, and resources). This study also proposes an effective collaboration implementation model in handling public complaints with indications of corruption.

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