Analisis Model Peramalan Status Kredit Kendaraan Bermotor pada Astra Credit Companies (ACC) Cabang X Periode 2011

Authors

  • Tomy G. Soemapradja Bina Nusantara University
  • Prycillia Susanto Bina Nusantara University

DOI:

https://doi.org/10.21512/bbr.v3i1.1340

Keywords:

prediction, credit status, automotive, Astra Credit Companies (ACC)

Abstract

In order to increasing revenue, credit and financial institution, especially, automotive financing, gave lower interest rate. This, of course, will impact to the costumer with higher opportunity to have their dream which facilitated by those institutions. Despites to all economic risks and sales targets, credit and financial institutions have to empower their credit monitoring to anticipate earlier of credit defaults. Inspired by Altman’s research in 1968, about predicting bankruptcy of US companies, this research has purpose to determine which variable that significantly to the car loan status at Astra Credit Companies (ACC), and further continue to arrange prediction model of loan status and measure it’s accuracy level.. The statistic test shows there are 2 independent variables affect to dependent variable significantly, where model’s accuracy level achieves 100%.

Dimensions

Plum Analytics

Author Biographies

Tomy G. Soemapradja, Bina Nusantara University

Mangement Department

Prycillia Susanto, Bina Nusantara University

Management Department

References

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Published

2012-05-31
Abstract 267  .
PDF downloaded 229  .