Sistem Pendukung Keputusan Pemilihan Kamar Kos dengan Metode Saw dan Implementasi Machine Learning dengan Algoritma Extreme Gradient Boosting ( Studi Kasus : Wilayah Kecamatan Kebon Jeruk )

Abstract

In this online era, prospective tenants can use the internet to find a boarding house to live in. However, prospective tenants need a lot of time to choose a boarding house to live in because there are many criteria that must be sought. The solution to the problem is a decision support system. In this research, the decision support system uses the Simple Additive Weighting algorithm, and the system implements Extreme Gradient Boosting to predict boarding house prices and use them as criteria for the assessment process. The results show that this boarding house assessment system can help prospective boarding house tenants to get alternative boarding places obtained based on the criteria chosen by users in choosing a boarding place with the Simple Additive Weighting (SAW) method and the criteria for predicting boarding room prices which have 80.22% accuracy.