Sistem Rekomendasi Tempat Kos Mahasiswa Baru dengan Metode Naïve Bayes Berbasis Web

Abstract

Currently, STIKI Indonesia's marketing division has not implemented a system that can make it easier for new students to get information about boarding houses in the campus area, especially for new students outside the Bali area. Usually, the marketing team in informing boarding places for new students is always constrained by hours. Little socialization and the marketing team always conducts a survey first, so it takes too long. Information onboarding places are also not optimal. This research aims to design and build a boarding house recommendation system for new students using the Naive Bayes method. Therefore, the author intends to design and build a Boarding Place Recommendation Decision Support System for New Students using the Naive Bayes method with the Google Map feature and the desired price range to help students find boarding houses in the campus area. This system can also help the marketing team shorten the working time, which usually conducts a survey first to determine the boarding house. The implementation of the system was tested by the black box testing method with the results of black-box testing, and the system's functionality was by what had been designed.