Optimisasi Pengecekan Anomali pada Proses Job: Analisis Waktu dan Data untuk Identifikasi Anomali yang Efisien

Abstract

The use of services in various software program contexts has become vital. Anomalies, whether in small or large scale, can disrupt the function of a software and impact a company's business processes. Therefore, the process of anomaly identification is crucial to ensure optimal software performance. This research aims to optimize the anomaly identification process in software services at PT. XYZ Tbk. Currently, information about anomalies is obtained through manual checks by the system operator team, which involves checking each job one by one, consuming a lot of time and potentially leading to overlooked anomalies. This research presents a solution to address this issue by developing an optimization system for monitoring anomaly identification in job, enabling faster identification for maintaining system services stability.. The anomaly identification monitoring system is a web-based application built using the Prototyping methodology, PHP programming language, Yii2 framework, PostgreSQL database, WebSocket, and Control-M API. The result of this research is the developed anomaly identification monitoring system, capable of accelerate the identification process and accelerate information transfer using WebSocket.