Nur Ramadhan
STMIK Profesional Makassar

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IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR TERHADAP PENENTUAN RISIKO KREDIT USAHA MIKRO KECIL DAN MENENGAH Ida; Suardi Hi Baharuddin; Muhammad Faisal; Nur Ramadhan; Darniati
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 1 (2023): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i1.163

Abstract

This research was carried out in the context of implementing the K-NN algorithm so that a source of information can be produced as a basis for supporting decisions on initial credit applications by customers so that they can help cooperative managers more as knowledge of the progress of credit proposals that are carried out at the Micro, Small and Medium Enterprise Cooperative Service Office ( SMEs) South Sulawesi Province. The K-Nearest Neighbor algorithm is used to classify objects based on attributes and training samples. Among them, from k objects, the k-Nearest Neighbor algorithm uses neighbor classification as the predicted value. The results show that the algorithm produces a classification with a faster calculation time based on the prediction of customer data resulting from the calculation.