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Hybrid of machine learning-based multiple criteria decision making and mass balance analysis in the new coconut agro-industry product development

Author

Listed:
  • Siti Wardah
  • Mohammad Yani
  • Taufik Djatna
  • Marimin Marimin

Abstract

Product innovation has become a crucial part of the sustainability of the coconut agro-industry in Indonesia, covering upstream and downstream sides. To overcome this challenge, it is necessary to create several model stages using a hybrid method that combines machine learning based on multiple criteria decision making and mass balance analysis. The research case study was conducted in Tembilahan district, Riau province, Indonesia, one of the primary coconut producers in Indonesia. The analysis results showed that potential products for domestic customers included coconut milk, coconut cooking oil, coconut chips, coconut jelly, coconut sugar, and virgin coconut oil. Furthermore, considering the experts, the most potential product to be developed was coconut sugar with a weight of 0.26. Prediction of coconut sugar demand reached 13,996,607 tons/year, requiring coconut sap as a raw material up to 97,976,249.

Suggested Citation

  • Siti Wardah & Mohammad Yani & Taufik Djatna & Marimin Marimin, 2024. "Hybrid of machine learning-based multiple criteria decision making and mass balance analysis in the new coconut agro-industry product development," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 16(3), pages 264-283.
    • Handle: RePEc:ids:ijidsc:v:16:y:2024:i:3:p:264-283
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