KLASIFIKASI PENENTUAN KELAYAKAN PINJAMAN KOPERASI DENGAN ALGORITMA CART MENGGUNAKAN ALGORITMA ADABOOST - Muhammad Rendy Raihan; Yulison Herry Chrisnanto; Ade Kania Ningsih (Universitas Majalengka, 2022)
According to the Cooperative Bureau, cooperatives became a mainstay for the lower middle class to revive and stabilize their respective economies when the Covid-19 Pandemic broke out in Indonesia. Through savings and loan cooperatives, people can provide loans to cooperatives. In this case, cooperatives provide money lending services to their members, and certain conditions apply to determine which loans are eligible. In connection with this, the officer will analyze the loan by filling out a loan application form accompanied by certain requirements in each loan application. In a mechanism that is not simple, problems often arise when eligibility decisions are not appropriate, namely bad credit. This research aims to solve the problem by designing a data mining application with a function to determine the feasibility of giving loans to customers. The method used is the CART algorithm method and uses the Adaboost algorithm. The results of the application of the CART algorithm method optimized with Adaboost turned out to be able to classify the eligibility of cooperative lending well, simplify the mechanism in credit analysis activities and be able to provide accurate eligibility status, which is guaranteed by the accuracy results of CART and Adaboost.