The fisheries sector plays an important role in the Indonesian economy, especially in supporting national food security. Fish farming, including ponds, has great potential to increase food production. However, this sector faces various challenges, especially related to capital and low investment interest. In fact, this sector holds promising economic opportunities. Many pond owners have difficulty getting access to capital and are not yet optimally connected with potential investors. This study aims to design a prototype of an intelligent system that can connect landowners with investors efficiently. In designing the system, the researcher applied two analysis methods, namely Return on Investment (ROI) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The ROI method is used to analyze investment feasibility by calculating the projected profit of pond investment that is more open to potential investors. Meanwhile, the TOPSIS method is used to recommend the best investment alternatives to potential investors based on several criteria such as profit, capital, location, type of fish, and harvest time, so that it can help potential investors in making investment decisions. Based on the case study, Pond A obtained an ROI of 67.36% and based on the TOPSIS analysis, Pond A obtained the highest preference value (Vᵢ = 0.9203). This study uses the Research and Development (R&D) method and the results of this study are in the form of an initial system design that has not been fully implemented. The system design that applies the ROI and TOPSIS methods is expected to be the basis for developing a more comprehensive system in the next stage. This system not only offers innovative solutions in fish pond investment, but also presents a data-based decision-making model that increases transparency and efficiency of investment in the fisheries sector.
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