Development of a Website-Based Boarding House Recommendation System Surrounding UNESA Ketintang Using Simple Additive Weighting and Weighted Product Methods Approach

Abstract

Selecting an appropriate boarding house is often challenging for students around Universitas Negeri Surabaya (UNESA) Ketintang because each available option offers different advantages in terms of cost, location, facilities, and room dimensions. To address this issue, this research developed a web-based recommendation platform that applies the Simple Additive Weighting (SAW) and Weighted Product (WP) approaches to assist users in identifying suitable boarding houses based on multiple criteria. The system processed data from 30 boarding house alternatives, while criterion weights were determined using the Analytical Hierarchy Process (AHP). A comparative analysis was conducted to examine the consistency of ranking results generated by both methods. Experimental findings show that the rankings produced by SAW and WP demonstrate a very strong relationship, indicated by a Spearman correlation value of 0.92. In addition, User Acceptance Testing (UAT) produced an average satisfaction score of 85%, indicating positive user responses toward the usability and functionality of the developed system. The findings suggest that integrating SAW and WP within a decision support framework can provide reliable recommendation results and help students make boarding house selection decisions more effectively and systematically.