IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR TERHADAP PENENTUAN RISIKO KREDIT USAHA MIKRO KECIL DAN MENENGAH
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Jan 10, 2023
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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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Ida, Baharuddin, S. H., Faisal, M., Ramadhan, N., & Darniati. (2023). IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR TERHADAP PENENTUAN RISIKO KREDIT USAHA MIKRO KECIL DAN MENENGAH. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 4(1), 212-223. https://doi.org/10.35870/jimik.v4i1.163
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S. Arni and S. Disa, “Computing Group News Documents Using K-Means and K-Nearest Neighbor,” 2019, doi: 10.4108/eai.2-5-2019.2284616.
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M. H. L. Vo and Q. Hoang, “Transformation of uml class diagram into owl ontology,” J. Inf. Telecommun., vol. 4, no. 1, pp. 1–16, 2020, doi: 10.1080/24751839.2019.1686681.
E. R. Aquino, P. De Saqui-Sannes, and R. A. Vingerhoeds, “A methodological assistant for use case diagrams,” Model. 2020 - Proc. 8th Int. Conf. Model. Eng. Softw. Dev., pp. 227–236, 2020, doi: 10.5220/0008938002270236.
Y. Qu et al., “An integrated framework of enterprise information systems in smart manufacturing system via business process reengineering,” Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., vol. 233, no. 11, pp. 2210–2224, 2019, doi: 10.1177/0954405418816846.
R. Fauzan, D. Siahaan, S. Rochimah, and E. Triandini, “Automated Class Diagram Assessment using Semantic and Structural Similarities,” Int. J. Intell. Eng. Syst., vol. 14, no. 2, pp. 52–66, Apr. 2021, doi: 10.22266/ijies2021.0430.06.
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