CREDIT SCORING MENGGUNAKAN ALGORITMA CLASSIFICATION AND REGRESSION TREE (CART) DAN ARTIFICIAL BEE COLONY

IRAWAN, INDRA and Rini, Dian Palupi and Ermatita, Ermatita (2021) CREDIT SCORING MENGGUNAKAN ALGORITMA CLASSIFICATION AND REGRESSION TREE (CART) DAN ARTIFICIAL BEE COLONY. Master thesis, Sriwijaya University.

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Abstract

Berbagai teknik statistik dan machine learning telah digunakan untuk mengembangkan model prediksi keuangan .Dalam hal ini Penilaian kredit sangat berkaitan erat dalam hal prediksi kelayakan kredit. Karena tidak ada kesepakatan umum atas rasio keuangan sebagai fitur masukan untuk pengembangan model, banyak penelitian menganggap pemilihan fitur sebagai langkah pra-pemrosesan dalam data mining sebelum membuat model.Penelitian ini menguji pengaruh seleksi fitura menggunakan Artificial Bee Colony terhadap peningkatan performa algoritma CART. Hasil eksperimental menunjukkan bahwa ABC merupakan kombinasi terbaik dari pemilihan fitur dalam meningkatkan performa algoritma CART . Dibandingkan dengan beberapa algoritma optimasi PSO dan Ant Colony metode yang diusulkan menunjukkan kinerja yang luar biasa.Hasil pengujian dengan 2 jenis dataset menunjukan tingkat akurasi CART + ABC dengan akurasi 80% dan 82%.Dengan adanya penelitian ini diharapkan dapat menjadi sebuah rujukan dalam hal penilaian kredit ,memungkinkan bank untuk menolak calon peminjam dengan kelayakan kredit yang buruk.

Item Type: Thesis (Master)
Uncontrolled Keywords: Credit Scoring, CART, ABC, Seleksi Fitur, Data Mining
Subjects: Q Science > Q Science (General) > Q1-295 General
Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions: 09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User: Indra Irawan
Date Deposited: 29 Nov 2021 04:22
Last Modified: 29 Nov 2021 04:22
URI: http://repository.unsri.ac.id/id/eprint/58066

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