Ayuputri, Ikacipta Mega (2018) Pemodelan Frekuensi Pembayaran Kredit Mobil di PT. X dengan Bayesian Geometric Regression dan Bayesian Mixture Geometric Regression. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Hadirnya layanan jasa dari lembaga pembiayaan bertujuan untuk menyediakan alternatif pembiayaan pembelian barang yang diinginkan, salah satunya pembelian mobil. Perusahaan pembia-yaan mengandalkan perbankan dan lembaga keuangan guna memenuhi kebutuhan sumber dana. Dalam melakukan penge-lolaan kreditnya, PT. X menghadapi berbagai masalah, salah satunya permasalahan nasabah gagal bayar (default). Salah satu langkah yang dapat dilakukan untuk meminimalisir terjadinya resiko tersebut adalah dengan melakukan pemodelan terhadap faktor penyebabnya ditinjau dari frekuensi pembayaran kredit oleh nasabah hingga mencapai batas toleransi yang diberikan oleh PT. X dimana frekuensi tersebut berdistribusi geometri. Pemodelan dilakukan dengan Bayesian Geometric Regression dan Bayesian Mixture Geometric Regression dimana kedua model menunjukkan variabel yang berpengaruh signifikan adalah status perkawinan, uang muka, lama angsuran, lama menempati tempat tinggal, dan besarnya premi asuransi. Model Bayesian Geometric Regression lebih baik dalam memodelkan frekuensi pembayaran kredit karena memiliki nilai DIC paling kecil. =============================================================================================== The existence of multifinance companies provide an alter-native financing on the purchase of goods. One of them is the pur-chase of cars. Multifinance companies rely on banks and financial institutions as source of their funds. In distributing funds to custo-mers as credit, multifinance companies has two necessary risks, prepayment risk and default risk. PT. X is one of the used car multfinance companies. In conducting credit management, PT. X faced various problems, one of them is the failure of customers to make credit payment (default risk). Therefore, to minimize the default risk is determine the factors that affect survival of custo-mers to make credit payment, in terms of frequency of credit pay-ments by customers that are distributed geometry. The modelling using Bayesian Geometric Regression and Bayesian Mixture Geo-metric Regression. The best model of this research is modelling using Bayesian Geometric Regression method because has lower DIC values than Bayesian Mixture Geometric Regression. Model-ling using Bayesian Geometric Regression show the significant variables are marital status, down payment, installment length, length of stay, and insurance.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Bayesian, Geometric Regression, Kredit Macet, Lembaga Pembiayaan, Mixture Model |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA31.3 Regression. Correlation H Social Sciences > HA Statistics > HA31.7 Estimation H Social Sciences > HG Finance > HG4012 Mathematical models |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Ikacipta Mega Ayuputri |
| Date Deposited: | 21 Jul 2021 22:49 |
| Last Modified: | 21 Jul 2021 22:49 |
| URI: | http://repository.its.ac.id/id/eprint/57534 |
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