<![CDATA[Automated Teller Machines (ATMs) generate large volumes of transaction log data, making manual identification of failed cash withdrawal transactions inefficient and error-prone. This study developed ATM Log Validator, a web-based application that automatically validates, filters, and displays failed cash withdrawal transactions from JSON log files. The application was built using HTML, CSS, and JavaScript with a client-side processing approach, ensuring that all data remain within the user's browser to enhance data privacy. The Prototype development method was employed, and system functionality was evaluated using Black Box Testing. Performance was assessed using a simulated dataset of 2,000 transaction logs generated from 50 ATM units across nine locations representing the operational environment of Bank Papua Manokwari Branch during 2021–2024. All functional test scenarios achieved a 100% success rate. The analysis identified 700 cash withdrawal transactions, including 85 failed transactions (12.14%). Failure rates declined from 13.92% in 2021 to 8.38% in 2024, with the highest rates recorded at Hotel Fajaroon and SPBU Jalan Baru. These results demonstrate that the application effectively supports ATM transaction auditing and reconciliation without requiring additional server infrastructure]]>
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