Halal Detection Kit Production: Economic Feasibility and Risk-Based Investment Planning

Background: Background: Indonesia’s halal industry offered strong growth potential, yet investment in halal detection tools remained limited. Strengthening this sector could improve independence and competitiveness in domestic biotechnology.Purpose: The study evaluates the financial feasibility of investing in the development of halal detection kit products and integrates risk management to enhance decision-making in biotechnology investments.Design/methodology/approach: A quantitative analysis was conducted using primary data (semi-structured interviews with PT XYZ’s management and company financial statements) and secondary data (literature, market reports, and internal documents). Investment feasibility was assessed through Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PBP). Monte Carlo simulations were applied to model uncertainty and integrate risk analysis into the NPV-at-Risk framework.Findings/Result: The study results show that the investment in developing halal detection kit products is economically feasible, as indicated by a positive NPV, an IRR above the discount rate, and a relatively short PBP. Monte Carlo simulations highlight the sensitivity of investment profitability to fluctuations in raw material prices and currency exchange rates, emphasizing the importance of effective risk management strategies.Conclusion: PT XYZ can reduce cost risk by collaborating with local partners to increase the Domestic Component Level (TKDN) and minimize reliance on imported raw materials affected by currency fluctuations. Implementing risk mitigation strategies based on the NPV-at-Risk method can optimize operations, improve cost efficiency, and expand market reach.Originality/value (State of the art): This research combined financial feasibility with risk-based analysis using the NPV-at-Risk method in biotechnology. Keywords: biotechnology, risk-based investment, halal detection kit, risk management, Monte Carlo simulation