IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR TERHADAP PENENTUAN RISIKO KREDIT USAHA MIKRO KECIL DAN MENENGAH
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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.
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Author Biographies
Program Studi Ilmu Komputer, STMIK Profesional Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia
Program Studi Manajemen Informatika, STMIK Profesional Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia
Program Studi Ilmu Komputer, STMIK Profesional Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia
Program Studi Ilmu Komputer, STMIK Profesional Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia
Program Studi Sistem Informasi, STMIK Profesional Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia
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