Open AccessGIS for coffee shops classification and routing using Naive Bayes method
Author(s) -
Erfan Rohadi,
A Amalia,
Johan Diaz Bagaskara,
Budi Harijanto,
Supriatna Adhisuwignjo
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/732/1/012079
Subject(s) - naive bayes classifier , coffee shop , computer science , selection (genetic algorithm) , operations research , business , marketing , artificial intelligence , mathematics , support vector machine
In recent years, the number of coffee shops has grown rapidly in Malang whose locations spread in various places. This condition makes the consumers having trouble to find the place that meets with their needs of the price and comfort level. In this works, the Geographical Information System of Coffee Shop Business Classification in Malang based on criteria is proposed. This system can classify coffee shop data according to the consumer desires using the Naïve Bayes method. Users simply provide a choice of price criteria and desired level of comfort on this website-based system. The classification results are used to make it easier for users to obtain information, both the map of locations and the route to reach the coffee shops that meet the criteria expected by the user. Based on the testing that has been done, 100% of users stated that they could find a coffee shop according to the desired criteria. As a result, the system promises as the application in determining the selection of coffee shops corresponds to the consumer criteria.