Information System for Culinary Product Selection Using Clustering K-Means and Weighted Product Method

DOI

10.2991/iccsr-18.2018.5How to use a DOI?

Keywords

decision support system; data mining; k-means; weighted product; culinary

Abstract

Typical foods are foods that have characteristics that cannot be found in other areas. The number of restaurants that sell typical food made consumers confused in choosing where to buy foods. This study aims to build information systems to provide culinary product recommendations based on the criteria desired by consumers. The clustering process used the k-means method used to classify the categories of food desired by consumers into six categories: appetizers, soups, desserts, snacks and drinks. In addition to the k-means clustering method, we also used a weighted product method that serves as a culinary selection recommendation rank. The result of the research is a system that can be used for culinary selection by using criteria of food category, number of menu, price, facility and distance. Case study was conducted in Semarang culinary tour. The result of clustering obtained from this research is there are 17 special dinning house entrees, 6 specialty soup restaurants, 51 restaurants selling staple dishes, 11 selling desserts, 13 restaurants selling snacks and 6 restaurants selling specialty drinks. While the weighted product method produces Wingkorolls as the first restaurant recommendation for dessert menu with a score of 0.2267.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Anindya Khrisna Wardhani
AU  - Catur Edi Widodo
AU  - Jatmiko Endro Suseno
PY  - 2018/07
DA  - 2018/07
TI  - Information System for Culinary Product Selection Using Clustering K-Means and Weighted Product Method
BT  - Proceedings of the International Conference of Communication Science Research (ICCSR 2018)
PB  - Atlantis Press
SP  - 18
EP  - 22
SN  - 2352-5398
UR  - https://doi.org/10.2991/iccsr-18.2018.5
DO  - 10.2991/iccsr-18.2018.5
ID  - Wardhani2018/07
ER  -