IMPLEMENTASI SISTEM MANAJEMEN KAS UNTUK MITIGASI IDLE CASH PADA MESIN ATM

Abstract

Cash management at Automated Teller Machines (ATMs) is a crucial aspect in maintaining a balance between liquidity efficiency and the quality of banking services. One of the main problems in ATM cash management is idle cash, which is cash that is not being utilized optimally, incurring opportunity costs, increasing operational costs, and increasing security risks. This study aims to examine the concept and mechanisms of a Cash Management System (CMS) in ATM cash management, identify the factors causing idle cash, evaluate the forecasting and optimization methods used in the CMS, and examine the effectiveness of their implementation based on a literature review. This study used a literature review approach by reviewing various relevant scientific journals, books, and academic publications. The results indicate that the CMS is an integrated system consisting of a forecasting module, an optimization module, and a monitoring and reporting module. Forecasting methods such as moving averages, exponential smoothing, ARIMA, and machine learning-based approaches play a role in improving the accuracy of cash requirement predictions. Meanwhile, optimization techniques such as linear programming and heuristic approaches are used to determine the optimal cash replenishment amount and schedule. Literature findings indicate that implementing a CMS supported by good data quality and appropriate control parameters can reduce idle cash levels, improve cash planning accuracy, and maintain cash availability (service level). Therefore, effective CMS implementation can improve operational efficiency and overall liquidity management in banking.