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PENERAPAN ALGORITMA NEAREST NEIGHBOR UNTUK PENENTUAN RISIKO PEMINJAMAN UANG SECARA ONLINE

Andiani Andiani(1*)
(1) Universitas Pancasila
(*) Corresponding Author
DOI : 10.35889/jutisi.v7i3.304

Abstract

Abstrak Sejalan dengan pertumbuhan teknologi yang sangat cepat, banyak bisnis-bisnis yang mulai memanfaatkan teknologi dalam penerapannya di kehidupan masyarakat. Peminjaman secara online merupakan masalah baru yang menarik untuk diteliti. Beberapa riset pemanfaatan teknologi komputer untuk mengurangi risiko peminjaman uang secara online telah banyak dilakukan dalam rangka menghindari dan mengurangi kehancuran suatu perusahaan pembiayaan secara online. Paper ini membahas algoritma Nearest Neighbor (kNN) yang diterapkan pada data konsumen yang menggunakan layanan peminjaman secara online. Hasil testing untuk mengukur performa algoritma ini berdasarkan tabel sample nasabah yang telah dikumpulkan untuk menghitung nilai kedekatan tertinggi adalah pada nilai kedekatan dengan kasus 1. Jadi, untuk uji coba data baru atas nama “Didu: maka nasabah pada nilai atribut keterangannya bernilai “Ya”. Kata kunci : Nearest Neighbor, Money Risk

ABSTRACT In line with the rapid development of technology, many businesses have begun to use technology in its application in people's lives. Online borrowing is an interesting new problem to be allocated. Several studies using computer technology to reduce the risk of borrowing money online have been done in order to avoid and reduce the destruction of online finance companies. This paper discusses the Nearest Neighbor (kNN) algorithm applied to consumer data that uses online loan services. The test results to measure the performance of this algorithm based on the sample tables that have been collected to calculate the highest proximity value on the value of closeness to case 1. So, to test new data on behalf of "Didu”: then find the value according to the definition requested "Yes". Keywords: Nearest Neighbor, Money Risk

References


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