The requirement for smooth information such as buying and selling is essential for commodity warehouse receipt system such as dried seaweed and their stakeholders to transact for an operational transaction. Transactions of buying or selling a commodity warehouse receipt system are a risky process due to the fluctuations in dynamic commodity prices. An integrated system to determine the condition of the real time was needed to make a decision-making transaction by the owner or prospective buyer. The primary motivation of this study is to propose computational methods to trace market tendency for either buying or selling processes. The empirical results reveal that feature selection gain ratio and k-NN outperforms other forecasting models, implying that the proposed approach is a promising alternative to the stock market tendency of warehouse receipt document exploration with accurate level rate is 95.03%.