GIS for coffee shops classification and routing using Naive Bayes method

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E. Rohadi, A. Amalia, J.D. Bagaskara, B. Harijanto, S. Adhisuwignjo

2020 IOP Conference Series: Materials Science and Engineering Vol. 732 Issue 1 Conference paper Cited by 2 SDG 8 Quartile

Abstract

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. © Published under licence by IOP Publishing Ltd.

Affiliations

Information Technology Department, State Polytechnic of Malang, Jl. Soekarmo Hatta No. 9, Malang, 65141, Indonesia; Electrical Engineering Department, State Polytechnic of Malang, Jl. Soekarno Hatta No. 9, Malang, 65141, Indonesia

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