<![CDATA[Abstract. The Consumer Cooperative of IKOPIN University (IU-Coop) operates several business units, with the Savings and Loan Unit (USP) contributing the most to the cooperative’s financial performance. However, unpredictable loan requests and reliance on member deposits have led to cash flow instability. To address this issue, this study proposes a predictive model for loan demand using the Non-Homogeneous Poisson Process (NHPP), which effectively models random events with time-varying intensity. Additionally, the Johnson SB distribution is employed to model loan amounts constrained within a specific range, while the Generalized Pareto distribution is used to represent the distribution of disbursement times, capturing the possibility of extreme delays. The dataset comprises short-term loan records from January 2022 to October 2024, with variables including loan amount (X) and disbursement duration (N). The analysis reveals that borrowers in Group 1 (loans under IDR 5,000,000) are expected to request two disbursements by the end of December 2024, requiring a total fund preparation of IDR 5,598,828. This modeling approach enhances liquidity management by providing more accurate forecasts and supports data-driven decision-making in microfinance operations.]]>
Copyrights © 2026
