Implementasi Algoritme Naïve Bayes Berbasis Particle Swarm Optimization Dalam Penentuan Pemberian Kredit

Muhammad Husni Rifqo, Nuri David Maria Veronica

Abstract


Sewa guna usaha (leasing) atau sering disingkat SGU adalah kegiatan pembiayaan dalam bentuk penyediaan barang modal baik secara sewa guna usaha dengan hak opsi (finance lease) maupun sewa guna usaha (lessee) selama jangka waktu tertentu berdasarkan pembayaran secara angsuran, kegiatan ini bisa dikatakan sebagai kegiatan kredit, kredit adalah penyediaan uang atau tagihan yang dapat dipersamakan dengan itu, berdasarkan persetujuan atau kesepakatan pinjam meminjam antara lembaga keuangan dengan pihak lain yang mewajibkan pihak peminjam melunasi utangnya setelah jangka waktu tertentu dengan pemberian bunga.Pengajuan aplikasi kredit oleh calon pelanggan sekarang sangatlah mudah, hal ini dikarenakan pengajuan kredit bisa dilakukan oleh semua orang sepanjang memenuhi syarat tertentu. Persaingan perusahaan penyedia kredit menjadi sangat pesat dan prediksi konsumen kredit adalah hal yang sangat penting. Dari permasalahan ini diperlukan suatu model yang mampu mengklasifikasikan sekaligus memprediksi pelanggan mana saja yang bermasalah dan tidak bermasalah. Model Naïve Bayes berbasis Particle Swarm Optimization (PSO) ternyata mampu meningkatkan akurasi dalam menganalisa kelayakan kredit, semakin besar data set yang digunakan maka akurasi model Naïve Bayes berbasis Particle Swarm Optimization (PSO) akan semakin meningkat, akurasi yang didapat oleh model ini untuk data set yang digunakan adalah: Agiing 2010 (96,75%), Agiing 2011 (97,95%), Japan credit approval (84,77%) dan Australia credit approval (87,83%).

Kata Kunci: Analisa kredit, penilaian kredit, Naïve Bayes berbasis PSO.


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DOI: https://doi.org/10.33369/pseu.6.1.1-12

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