Uji Algoritma Random Forest Pada Dataset Online Shoppers Purchasing Intention - Purnama, Arif; Maulana Yusup, Ali; Wibowo, Agung; Susilawati, Desi (IKRA-ITH Informatika : Jurnal Komputer dan Informatika, 2020)
Online shopper is an online shopping that is currently being done by almost everyone. Shopping online can simplify the transaction process without having to meet directly with the seller. Many studies have been conducted in testing online shopper purchasing intention, one of which is research conducted by C. Okan Sakar in 2018 which used the naive bayes and random forest methods. Several previous studies concluded that most of the datasets used were not resample first. To obtain higher accuracy with Random Forest, Resample the dataset into 2 parts, namely for Training 60% of the dataset and 40% for Testing. As a result, by resample the dataset first, it can be concluded that the accuracy is higher than the dataset that was not resample first. By doing the comparisons, it also shows that Random Forest gets better results than other algorithms