Limited capital is a major obstacle in investment decision-making, especially for novice investors. This study aims to develop an optimization model for investment fund allocation with limited capital using an operations research approach (linear programming) and its implementation through Orange Data Mining. A case study was conducted on three digital investment instruments (stocks, mutual funds, gold) with a total capital of IDR 100 million and a maximum risk limit of 10%. The method used is linear programming solved using the Simplex method and Orange Data Mining. The results showed an optimal solution of 25% stocks, 50% mutual funds, 25% gold with an expected return of IDR 10.75 million/year. Method comparison showed identical accuracy (100%) with Orange computation time of 0.3 seconds vs 15 minutes manually. Sensitivity analysis revealed that increasing risk tolerance from 10% to 15% increases returns to IDR 12.5 million. This research contributes to the development of investment decision support tools that are easy to use by novice investors as well as teaching materials for Operations Research.
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