Perbandingan Prediksi Performance Kredit Pada Peer to- Peer Lending Syariah Dengan Ensemble Dan WoE IV

• ACHMAD RIVANI FAUZI
• 14210186

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ABSTRAK

ABSTRAK

Nama              : Achmad Rivani Fauzi

NIM                 : 14210186

Program Studi : Ilmu Komputer

Fakultas          :Teknologi Informasi

Jenjang           : Strata Dua (S2)

Konsentrasi     : Data Mining

Judul              : “Perbandingan Prediksi Performance Kredit Pada Peer to- Peer Lending Syariah Dengan Ensemble Dan WoE IV” Peer to peer lending Syariah merupakan bentuk pinjam-meminjam berbasis Syariah yang menyediakan layanan pinjam-meminjam sesuai prinsip Syariah, serta menawarkan opsi investasi dengan potensi keuntungan lebih tinggi melalui skema bagi hasil. Namun dalam pemberian kredit sering terjadi kredit macet yang disebabkan oleh gagalnya pembayaran atau pengembalian dari nasabah, masalah ini dapat terjadi oleh Lembaga Keuangan manapun ketika memberikan kredit. Dengan memanfaatkan data mining dan algoritma machine learning, penelitian ini akan memfokuskan analisis pada variabel-variabel yang relevan untuk memprediksi kelayakan kredit.dan memberikan prediksi performa kredit. Langkahlangkah yang diambil meliputi mengumpulkan data tentang pemahaman bisnis, menyiapkan data, memproses fitur-fitur, dan mengolah data agar menghasilkan prediksi yang akurat. Hasil menunjukan akurasi algoritma Ensemble sebesar 97,54%, Decision Tree 82,75%, Random Forest 81,30%, dengan penambahan metode Weight of Evidence dan Invformation Value.

KATA KUNCI

Peer to peerlending syariah,Kredit Macet,Ensemble,Decision Tree,Random Forest

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DAFTAR PUSTAKA

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