Rekomendasi Lokasi Wisata Kuliner Menggunakan Metode K-Means Clustering Dan Simple Additive Weighting

Saksono, Nugroho Dwi (2018) Rekomendasi Lokasi Wisata Kuliner Menggunakan Metode K-Means Clustering Dan Simple Additive Weighting. Sarjana thesis, Universitas Brawijaya.

Abstract

Melakukan wisata kuliner merupakan salah satu kegiatan yang sering dilakukan ketika mengunjungi suatu kota. Kesalahan dalam memilih sebuah lokasi wisata kuliner yang ingin dikunjungi dikarenakan kurangnya informasi terhadap lokasi apa saja yang tersedia menjadi masalah bagi wisatawan yang ingin merasakan kepuasan berwisata kuliner. Tujuan penelitian ini adalah membantu para wisatawan dalam menentukan lokasi wisata kuliner yang memilki fasilitas yang sesuai dengan yang diinginkan. K-Means Clustering merupakan sebuah metode yang mengelompokan data sesuai dengan cluster masing-masing. Simple Additive Weighting (SAW) adalah metode yang digunakan untuk proses pemeringkatan dengan menggunakan nilai preferensi. Dalam penelitian ini, metode K-Means Clustering akan membagi lokasi wisata sesuai jarak yang dihitung dari posisi awal user ke alamat lokasi wisata, lalu metode SAW akan mengurutkan lokasi mana yang paling sesuai dengan keinginan user. Data yang digunakan untuk pengujian menggunakan 49 data lokasi. Pengujian yang dilakukan adalah pengujian akurasi dengan membandinkan hasil yang dikeluarkan oleh sistem dengan hasil yang dipilih oleh 30 responden. Pengujian tersebut mendapatkan hasil akurasi sebesar 63,33% untuk kategori sangat dekat, 40% untuk kategori dekat, 46,67% untuk kategori sedang. Sistem ini sudah bisa memberikan rekomendasi untuk kategori sangat dekat dengan cukup akurat walaupun untuk kategori dekat dan sedang masih belum cukup akurat.

English Abstract

Culinary tour is one of the activities that are often done when visiting a city. the mistakes often made because lack of information regarding a location of a culinary tourism can cause a problem for tourists. The purpose of this study is to help the tourists in determining the location of culinary tourism that has the facilities in accordance with what they desired. K-Means Clustering is a method that groups data according to their clusters. Simple Additive Weighting (SAW) is a method for the ranking process by using a preference value. In this study, K-Means Clustering method will divide the location according to the distance calculated from the initial position of the user to the address of the location, then SAW method will sort which location best suit the user’s wishes. The testing used 49 location data. The testing process is a accuracy test by comparing result from the system and results from 30 respondents. The results of the testing process is obtained an accuracy of 63.33% for very close category, 40% for near category, and 46,67% for medium category. This system can provide recommendations for very close categories with fairly accurate although for the near and medium category is still not accurate enough.

Item Type: Thesis (Sarjana)
Identification Number: SKR/FTIK/2018/201/051801223
Uncontrolled Keywords: Lokasi, Wisata Kuliner, Pendukung Keputusan, K-Means Clustering, SAW
Subjects: 000 Computer science, information and general works > 004 Computer science > 004.015 1 Finite mathematic
Divisions: Fakultas Ilmu Komputer > Teknik Informatika
Depositing User: Yusuf Dwi N.
Date Deposited: 28 May 2018 04:02
Last Modified: 27 Oct 2021 03:51
URI: http://repository.ub.ac.id/id/eprint/11181
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