Green Supply Chain Productivity Modeling for Oyster Mushrooms Agroindustry Improvement

Association Rules Mining, Green Productivity, Oyster Mushrooms, Relief, Supply Chain

Authors

  • Ma'ruf Pambudi Nurwantara Department of Agrotechnology, Faculty of Agricultural, Merdeka Madiun University, Jalan Serayu, Madiun, East Java, 63133, Indonesia
  • Luluk Sulistiyo Budi Department of Agrotechnology, Faculty of Agricultural, Merdeka Madiun University, Jalan Serayu, Madiun, East Java, 63133, Indonesia
  • Nunik Hariyani Department of Communication Studies, Faculty of Social and Polotical Sciences, Merdeka Madiun University, Jalan Serayu, Madiun, East Java, 63133, Indonesia
  • Dian Ardifah Iswari Department of Bio-Entrepreneurship, Faculty of Formal and Applied Sciences, Muhammadiyah University of Madiun, Jalan Mayjend Panjaitan, Madiun, East Java, 63137, Indonesia
July 1, 2022
July 18, 2022

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Oyster mushrooms agroindustry in Indonesia have been potential in an effort to support local economic development. The objectives in this paper are to analysis the requirement of system design green productivity oyster mushrooms supply chain, to select the important attributes and to determine development strategies for increased green productivity. In order to analyze the requirement system, use case diagram and Business Process Model and Notation (BPMN) were used in this paper. Relief method was used to select the important parameter attributes which sufficiently describe environment variables affecting the upstream and downstream supply chain of oyster mushroom. Then, to establish the rule in the formation of strategy formulation, Association Rules Mining was applied. The results are analysis in this paper system with BPMN business flow diagram can describe the system more easily. Relief method shows that the most important economic variable is sawdust. Association Rules Mining shows that economic variables with high corn and high ring was produced low sawdust with 100% confidence level and support value of 0.167 This research is expected to facilitate prediction of strategy to increase productivity oyster mushroom agroindustry based on existing environment condition.