Multi-Criteria Recommender System for Optimization Product Based on Automatic Execution of Smart Contracts in a Blockchain Serious Game

Authors : Astrid Novita Putri, Paulus Harsadi, Dwi Remawati, Reza Fuad Rachmadi, Sony Aditya

Pages : 57-69

Doi:10.57020/ject.1645722

View : 128 | Download : 125

Publication Date : 2025-12-31

Article Type : Review Paper

Abstract :Agriculture is one of the main livelihoods in Indonesia. The country is a major producer of soybean and corn; however, the production output is still suboptimal due to the imbalance between consumption and production. This research integrates Multi-Criteria Recommender System (MCRS) for production optimization with blockchain-based smart contracts in the context of serious games. MCRS is used to evaluate various key factors to generate decision-making recommendations for farmers, optimizing production based on production and consumption levels, with the aim of maximizing farmers\\\' stocks and meeting consumer needs. The approach is simulated in a serious game, with automatic execution of blockchain smart contracts using computer protocols without third-party involvement, ensuring transparency and data security in optimizing the entire production chain automatically and in real time. Optimization is performed using the Multi-Objective Optimization (MOO) method with a simplex function, where Z1 aims to maximize production based on average production, and Z2 aims to maximize production based on average consumption. The developed method uses Weighted Sum for decision-making value and Pareto Front method to optimize multiple issues by finding a solution that meets all objectives. The results showed that production optimization using simplex method resulted in values of Z1 = 7,591.044 and Z2 = 854.598 stocks per capita, with a trade-off value of 57.745. Using the simplex method for the optimization results of the average consumption of 854,598 stock per person/ per capita in 1 year based on the average consumption, it will get an average number of consumptions for soybean and corn commodity. These values indicate a significant increase in production efficiency as the system is able to maintain a balance between the production capacity of farmers and the consumption needs of the community. The Z1 value reflects the increase in stock availability from the farmers\\\' side, while Z2 shows the efficiency in meeting per capita consumption needs. The trade-off value describes the optimal compromise point achieved between the two objectives, supporting the achievement of balance in the agricultural product distribution system. In addition, the implementation of blockchain technology in the agricultural production process contributes significantly to data transparency, security, and efficiency. By utilizing the Tezos Blockchain Network Environment, Unity 3D 2021.3.18f1, Solidity programming language based on Web 3 technology, and Redis Enterprise and MongoDB Compass databases, the system is able to record and execute transactions automatically without manual intervention. This strengthens trust between actors in the supply chain and supports a sustainable digital agriculture ecosystem.
Keywords : Pareto Front, Simpleks, Data flow optimization, computational efficiency algorithm design, Multi-Criteria Recommender System, Blockchain, Serious Game

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