Nurul Ramadiah Madjid
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru

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Sistem Rekomendasi Hotel Di Provinsi Riau Dengan Metode AHP dan SAW Nurul Ramadiah Madjid; Yelfi Vitriani; Elin Haerani; Fitra Kurnia
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.931

Abstract

Riau Province is one of the provinces that has been equipped with various recreational facilities, sports facilities and tours that are very interesting to visit. With the increasing number of facilities and tourist attractions that can be visited, the hotel is one place that is needed as a lodging facility. Hotels in Riau Province are also growing very rapidly. Riau provides so many choices of hotels scattered in various locations with various hotel classes, rental prices, facilities and services. The system is a set of components and combined elements, organized and collaborative components to achieve a certain goal, namely providing information. AHP is a decision support model that will describe complex multi-factor or multi-criteria problems into a hierarchy. The SAW method is known as the term weighted sum. The basic concept of the SAW method is to find the weighted sum of the performance ratings for each alternative on all attributes. The results obtained from this system are systems that are made into the good category by applying the AHP and SAW methods. The Hotel Recommendation System in Riau Province with the AHP and SAW Methods can help the Tourism Office and the community in selecting hotels. The Hotel Recommendation System using the AHP and SAW methods has been able to produce hotel recommendations in Riau Province according to needs and based on criteria determined by the user. Based on the Black Box testing, it shows that the system can run well with its functions, and with the UAT testing that has been carried out, a result of 82% is obtained where the results fall into the strongly agree category