IDENTIFYING POTENTIAL LEADING PRODUCTS IN SAMARINDA CITY: A BAYESIAN ANALYSIS AND CLUSTER SCORING APPROACH
IDENTIFIKASI PRODUK UNGGULAN KOTA SAMARINDA MENGGUNAKAN ANALISIS BAYES DAN SKORING KLASTER
DOI:
https://doi.org/10.54902/1989yb77Keywords:
Superior Products, Bayes Analysis, Micro Analysis, Product Scoring, Local Economic DevelopmentAbstract
This study aims to identify and prioritize superior products at the micro-level in Samarinda City to support evidence-based regional economic development policies. While macro-sectoral analysis provides a broad overview, identifying specific, high-potential products at the district level is crucial for targeted interventions and downstreaming. This research utilizes a micro-qualitative and quantitative approach, collecting primary data through in-depth interviews, Focus Group Discussions (FGD), and field observations involving local business actors and stakeholders. The method involves two main stages: first, Product Cluster Analysis using a scoring system based on criteria such as labor absorption, economic contribution, and market control; second, Bayes Analysis to assess the feasibility and potential of products in each district based on input, process, and output parameters. The results of the scoring analysis show that Brown Sugar (Gula Merah) has the highest score (34.5), followed by Wooden Shipyards, Hospitality, and the Pampang Cultural Village (all 34). The Bayes analysis further identifies specific potential products per district, such as Essential Oils in Palaran (2.24), Brown Sugar in Sambutan (2.56), and Dayak Crafts in North Samarinda (2.38). This study recommends a downstreaming and diversification strategy focused on these identified superior products to increase added value and local competitiveness
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