Indikasi Penyimpangan Laporan Keuangan Akademik Universitas XYZ Menggunakan Algoritma Greedy dan K-Means

  • Lukman Hakim Universitas Bunda Mulia
  • Harvin Seruni Universitas Bunda Mulia
##plugins.pubIds.doi.readerDisplayName##: https://doi.org/10.29207/resti.v2i1.261
Keywords: greedy algorithm, K-Mean clustering, deviation

Abstract

Financial deviation are often found in various agencies as occurred in 16 PTN (Merdeka.com) in the financial reporting of a lot of unfairness in the BPK (Supreme Audit Agency) report, this happens because the mechanism of reporting in the internal University has no financial audit. It is necessary to create an application that can detect the occurrence of deviation in proposals and financial reports that impact on unnatural reports, this study using the Greedy and K-Mean Clustering algorithms. The application of academic financial detection at University XYZ has the function of making proposal, financial report, monitoring from the person in charge to facilitate supervision and the existence of notification if there is budget unreasonable. The application of Greedy and K-Mean algorithms to the application can be applied by simulating proposals and reports that have reasonable and unreasonable prices, showing success with the notification of each proposal and unnatural reports on finance.

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References

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Published
2018-04-16
Section
Technology Information Article