ABSTRAK
Memasuki dekade tahun 2000 industri jasa pembiayaan di Indonesia semakinberkembang pesat, karena lcebutuhan masyarakat akan alat transportasi yang praktis danmurah semakin tinggi. Sehingga perusahaan pembiayaan dituntut untuk dapatmenyesuaikan diri dengan kebutuhan masyarakat terhadap pelayanan jasa keuangan yangsangat kompleks. Penulis melakukan penelitian ini bertujuan untuk mengetahui pengaruhIncome, Age, Marital Status, Down Payment, Tenor don Interest terhadap kemungkinantegjadinya kredit gagal bayar, sehingga perusahaan pembiayaan melalui analisis kreditnyadapat mengidentifikasi konsu.men~konsumen yang layak untuk diberikan kredit agardapat meruinimalisir texjadinya gagal kredit.Pengujian dalam peneiitian dilakukan dengan menggunakan metode analisis logit denganmengambil data konsumen PT. ABC yang melakukan kredit sepeda motor sebanyak14,718 konsumen. Hasil dari penelitian ini rnenunjukkan Income, Age, Marital Status,Interest, Age terhadap Income, Income terhadap Marital Status, Age terhadap Incometerhadap Marital Status, DP terhadap Income dan Income terhadap Tenor signifikanterhadap kemunglcinan tenjadinya status kredit gagal bayar. Dari seluruh variabel iniIncome mempakan bagian terpenting dalam kredit dan pengaruh ketidakpastian di masayang akan datang sangat mempengaruhi konsumen terhadap kemungkinan default.

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Abstract
Entering the decade of 2000 financial services industry in Indonesia growingrapidly, because many people needs a practical transportation and low cost. Financingcompanies are required to be able to adjust to the needs of the communityof financial services that are complex. The Purpose of this paper is to understand theinfluence of Income, Age, Marital Status, Down Payment, Tenor and Interest on thestatus of credit failed to pay, so the company through financial analysis can identify theconsumer credit-worthy consumers who are given credit for in order to theoccurrence of failed credit.Logit analysis method was used in this study with the data consumers takes from PT.ABC is doing a motorcycle loan as 14,718 customers. Results from this research indicateIncome, Age, Marital Status, Interest, Age by Income, Income by Marital Status, Age byIncome by Marital Status, DP by Income dan Income by Tenor of a significant effect onthe status of credit failed to pay. From the all variable Income is the most important to getloan and the influence of uncertainty in the future greater influence on the consumer failsto pay the loans.