Fraud detection on event logs of goods and services procurement business process using Heuristics Miner algorithm

Dewi Rahmawati, Muhammad Ainul Yaqin, R. Sarno
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引用次数: 18

Abstract

Event logs are history records that contain sequence data for the activity of a case that has been executed by an information system. Event logs can be valuable information with a technique called mining process. With this technique, cheating on the business processes of an enterprise can be detected early on. Thus, the company can commit further examination of business processes, especially the business process of procurement of goods and services to achieve business process is expected.[8] In this study, management data of event log obtained from log data at each event transaction procurement and services. The event log data is then analyzed using a heuristic miner algorithm. Heuristics miner algorithm chosen because it has advantages that are not owned by Alpha++ algorithm that this algorithm can calculate the frequency relation between activities in the log to determine the causal dependency. Heuristic Miner can be used to determine the predominant process of thousands of logs and detect behaviors that are not common in a process.[11] This study aims to detect anomalies on business processes that occur during the process of procurement of goods and services by calculating the fitness value of the event log into the system. Heuristic miner algorithm using the results obtained identification accuracy of 0.88%.
基于启发式Miner算法的商品服务采购业务流程事件日志欺诈检测
事件日志是包含由信息系统执行的案例活动的序列数据的历史记录。通过一种称为挖掘过程的技术,事件日志可以成为有价值的信息。使用这种技术,可以及早发现企业业务流程中的欺骗行为。这样,公司就可以对业务流程,特别是采购商品和服务的业务流程进行进一步的检查,以达到业务流程的预期在本研究中,事件日志的管理数据是从每一个事件交易的日志数据中获得的。然后使用启发式挖掘算法分析事件日志数据。选择启发式挖掘算法是因为它具有Alpha++算法所不具备的优点,该算法可以计算日志中活动之间的频率关系,从而确定因果依赖关系。启发式Miner可用于确定数千条日志中的主要进程,并检测进程中不常见的行为。b[11]本研究旨在通过计算事件日志进入系统的适应度值来检测在商品和服务采购过程中发生的业务流程异常。利用启发式挖掘算法得到的结果识别准确率为0.88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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