Implementasi Klasifikasi Data Mining Untuk Penentuan Kelayakan Pemberian Kredit dengan Menggunakan Algoritma Naïve Bayes
DOI:
https://doi.org/10.30865/json.v4i1.4653Keywords:
Data Mining, Classification, Appropriateness, Credit, Naïve Bayes AlgorithmAbstract
Credit today is very widely used in the transaction process. At first, lending was only done by banks, but with the development of time and also the increasing needs and purchases from the public, lending is not only done by banks. The granting of credit for financing goods by the company to the buyer is not done haphazardly, but must go through several selection processes. The process of granting credit must be carried out through detailed and strict stages. This causes the process to be lengthy and also lengthens the work of the selection team. Data mining is a data processing technique that is useful for obtaining important patterns from data sets. The Naïve Bayes algorithm is part of the data mining classification process. The process of the Naïve Bayes algorithm is based on the concept of the Bayes theorem. The result of the research is that the new alternative data is ACCEPTABLE for credit applications, it can be seen that the probability value of ACCEPTED is greater than the probability value of REJECTED, which is 0.011108
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