Analisis Faktor-Faktor yang Mempengaruhi Risiko Gagal Bayar Debitur pada Lembaga Keuangan Mikro Menggunakan Regresi Logistik dan Ant Coloni Optimization (ACO)
DOI:
https://doi.org/10.15575/kubik.v7i1.13836Keywords:
Lembaga Keuangan Mikro, risiko gagal bayar, faktor risiko debitur, model regresi logistik, Ant Coloni Optimization (ACO).Abstract
Salah satu peranan langsung Lembaga Keuangan Mikro (LKM) terhadap industri kecil dan mikro adalah memberikan dana pinjaman berupa kredit kepada nasabah yang membutuhkan. Dalam hal ini nasabah LKM dapat mengajukan kredit dengan memenuhi persyaratan dari LKM lalu kredit didapatkan jika LKM menyetujui kesepakatan pinjaman. Dalam proses pemberian kredit yang dilakukan oleh LKM sering dihadapkan pada suatu risiko yang dikenal sebagai risiko kredit bermasalah (problem loans). Berdasarkan risiko gagal bayar tersebut, paper ini bertujuan untuk melakukan analisis faktor-faktor yang mempengaruhi risiko gagal bayar dari calon debitur. Metode yang digunakan adalah regresi logistic dan Ant Coloni Optimization (ACO). Terdapat beberapa tahap dalam penelitian ini: (1) melakukan standarisasi data pada data faktor risiko calon debitur, (2) menetapkan asumsi model regresi logistic, (3) melakukan estimasi parameter model regresi logistik menggunakan algoritma Ant Coloni Optimization (ACO), dan (4) melakukan uji signifikansi setiap variabel. Dalam paper ini, data yang digunakan adalah data historis debitur pada LKM di Bandung, Indonesia. Hasilnya menunjukkan bahwa lima faktor yang dianalisis berpengaruh signifikan terhadap risiko gagal bayar, yaitu usia, jumlah tanggungan keluarga, nilai jaminan, besarnya kredit yang diajukan, dan jangka waktu pengembalian kredit. dengan kekuatan korelasi sebesar 93.5%. Menggunakan lima factor ini, yang digunakan untuk menentukan probabilitas gagal bayar dari calon debitur. Probabilitas risiko gagal bayar calon debitur ini, sangat berguna bagi LKM guna menentukan klasifikasi faktor kelayakan pemberian kredit berdasarkan predikat risiko calon debitur. Demikian sehingga, LKM dapat mengetahui faktor-faktor risiko gagal bayar dan mengambil keputusan pemberian kredit yang layak atau tidak layak.
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