Restaurant Recommendation Decision Support System Using Topsis System

Nesya Rogawati, Indah Susilawati, Arita Witanti

Abstract


The vast technology development in the culinary aspect makes all kinds of information could be acquired easily. Information is needed to be one of some considerations when a person is going to book a seat in a restaurant. Hungryhub is restaurant booking service provider which helps customers to be able to make a reservation online. This research background is Hungryhub website development innovation which offers so many restaurants. The aim of this research is to help customers upon making decisions with restaurants' recommended option alternatives.

This research is using Technique for Other Reference by Similarity to Idea Solution (Topsis). Data is collected from documentation and interviews. The documentation is obtained from survey fulfillment by the users which would be processed and references of the restaurant recommendations for the users themselves.

The interviews are done with the Hungryhub operational team to get the restaurants' data which have cooperated with Hungryhub. The topsis method is chosen because it has a concept that chosen alternatives are alternatives which have the shortest range to the ideal positive solutions and have the farthest range to the ideal negative solutions. The result of this research is a recommendation system which could display alternative restaurants' ranking result.


Full Text:

PDF

References


Ariyanti, J., & Purnomo, A. S. (2019). Rekomendasi Pemilihan Produk Tabungan Bank Rekomendasi Pemilihan Produk Tabungan Bank. Informatics Journal, Vol. 4, No. 1, ISSN : 2503 – 250X, 1-9.

Kusrini. (2007). Konsep dan Aplikasi Sistem Pendukung Keputusan. Yogyakarta: Andi.

Kusumadewi, S., Hartati, S., Harjoko, A., & Wardoyo, R. (2006). Fuzzy Multi- Atribute Decision Making (Fuzzy MADM). Yogyakarta: Graha Ilmu.

Maria, A., & Purnomo, A. S. (2019). Sistem Pendukung Keputusan Pengajuan Kredit Menggunakan Simple Additive Weighting (SAW) (Studi Kasus Bank BPD DIY). Seminar Nasional Teknologi Informasi dan Aplikasi Komputer (SINTAK) (hal. 106-114). Semarang: Universitas Stikubank Semarang.

Mayasari, W., & Purnomo, A. S. (2017). Sistem Pakar Untuk Menentukan Poin Pelanggaran Dan Prestasi Menggunakan Inferensi Fuzzy (Tsukamoto). Jurnal Multimedia & Artificial Intelligence, Vol. 1, No. 2, Agustus, ISSN : 2580-2593, 17-26.

Nofriansyah, D., & Defit, S. (2017). Multi Criteria Decision Making (MCDM) pada sistem pendukung keputusan. Deepublish.

Priatni, C. N., & Purnomo, A. S. (2017). Sistem Untuk Menentukan Pilihan Pada Program Studi Menggunakan Fuzzy Multiple Attribute Decision Making (FMADM) Dengan Simple Additive Weighting (SAW) (Studi Kasus: POLTEKES Permata Indonesia Yogyakarta). Informatics Journal, Vol. 2, No. 1, ISSN : : 2503 – 250X, 54-63.

Purnomo, A. S., & Rozi, A. F. (2018). Seleksi Mahasiswa Lulusan Terbaik Menggunakan Metode Fuzzy Multi-Attribute Decision Making (FMADM) (Studi Kasus: Program Studi Teknik Informatika FTI UMB Yogyakarta). Seminar Nasional Teknologi Informasi Dan Aplikasi Komputer (SINTAK) (hal. 156-163). Semarang: Universitas Stikubank.

Rozi, A. F., & Purnomo, A. S. (2017). Rekomendasi Pemilihan Minat Studi Menggunakan Metode Mamdani Studi Kasus : Program Studi Sistem Informasi FTI UMBY. Informatics Journal, Vol. 2, No. 3, ISSN : 2503–250X, 138-147.

Septian, M. N., & Purnomo, A. S. (2017). Sistem Penilaian Pegawai Menggunakan Metode Fuzzy Multiple Attribute Decision Making (FMADM) dan Weighted Product (WP). JMAI (Jurnal Multimedia & Artificial Intelligence), Vol. 1, No. 1, ISSN : 2580-2593, 27-33.




DOI: http://dx.doi.org/10.36722/exc.v1i1.2248

Refbacks

  • There are currently no refbacks.