Penerapan Algoritma Naive Bayes dan Multiple Linear Regression Untuk Prediksi Status dan Plafon Kredit (Studi Kasus: Bank ABC)

Along with changing technology, Human resources are still needed in many parts of decision making. The companies and organizations use human to analysis data. Despite that performance, took longer time effort complete. And sometimes there is always a negative factor such as unmanageable human. Therefore, it’s important provide an excellent training source so this resource able reach outcome needed. Machine learning one the most common knowledge There forms machine regression, classification, clustering, etc. two which used application, regression classification. Naive Bayes classification method rooted on theorem. Naïve historical data predict future based characteristic Multiple Linear Regression involves more than independent variable or predictor. With resources, man can easily analyse credit worthiness determine limit bank costumer without taking long much effort.