Pemanfaatan Artificial Intelligence (AI) sebagai Sistem Pendukung Keputusan Berbasis Informasi di Badan Perencanaan Pembangunan Daerah (BAPPEDA) Provinsi Sumatera Barat
DOI:
https://doi.org/10.61722/jmia.v3i1.8212Keywords:
Artificial Intelligence, Decision Support System, Regional Development Planning, Data-Driven GovernanceAbstract
The rapid development of digital technology has significantly transformed public governance, particularly in regional development planning processes. One of the most strategic technologies in this transformation is Artificial Intelligence (AI), which enables large-scale data processing, predictive analysis, and information-based decision support. This study aims to analyze the utilization of AI as an information-based decision support system at the Regional Development Planning Agency (BAPPEDA) of West Sumatra Province. The research adopts a qualitative approach using a case study design. Data were collected through in-depth interviews, observation, and document analysis involving BAPPEDA officials and relevant stakeholders engaged in regional development planning. Data analysis was conducted using an interactive model consisting of data reduction, data display, and conclusion drawing. The findings indicate that the application of AI at BAPPEDA West Sumatra Province has contributed to improving data analysis capacity, enhancing work efficiency, and supporting the prioritization of regional development programs. AI functions as a strategic supporting tool by providing data-driven information and recommendations while maintaining human authority in final decision-making. However, the study also reveals several challenges, including limited data integration and quality, insufficient human resource capacity, and the absence of comprehensive governance and internal policies related to AI utilization. This study concludes that AI has significant potential to enhance the quality of regional development planning if supported by a robust data ecosystem, improved human resource competencies, and sustainable technology governance. The findings are expected to contribute to the development of data-driven planning practices in regional government institutions.
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