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

Siti Wardah, Mohammad Yani, Taufik Djatna and Marimin Marimin

International Journal of Information and Decision Sciences, 2024, vol. 16, issue 3, 264-283

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.

Keywords: coconut agro-industry; hybrid of machine learning; mass balance analysis; multiple criteria. (search for similar items in EconPapers)
Date: 2024
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