Fraud Detection of Bus Ticket Sales by Using Spatio Temporal Data Mining
Fajar Delli Wihartiko1, Doni Wihartika2
1Fajar Delli Wihartiko, Department of Computer Science, Universitas Pakuan, Indonesia.
2Doni Wihartika, Department of Management, Universitas Pakuan, Indonesia.
Manuscript received on 02 August 2019 | Revised Manuscript received on 25 August 2019 | Manuscript Published on 05 September 2019 | PP: 17-21 | Volume-8 Issue-2S7 July 2019 | Retrieval Number: B10040782S719/2019©BEIESP | DOI: 10.35940/ijrte.B1004.0782S719
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cheating in the sale of bus tickets is often found in transportation service providers who still use the conductor as a ticket seller on the bus. The high cost of supervision, lack of honesty, unification of the sales function and the ticket control function on the conductor makes this fraudulent practice a problem that companies must handle. By looking at the behavior of ticket sales for each individual through the method of spatio temporal clustering can detect fraudulent behavior that occurs. The bus ticket sales deception process is implemented in Bogor’s Bus Rapid Transit (BRT). The results show that there are 3.2% of high-potential officers cheating ticket sales. By knowing the cheating behavior of ticket sales, the company can follow up with the policy so that cheating behavior does not become the company culture.
Keywords: Conservation, Data Mining, C45.
Scope of the Article: Data Mining