Implementation of the K-Means Method in Grouping  Merchandise Locations at the Market Service

syawaludin pohan

doi:10.59934/jaiea.v1i2.74

Authors

syawaludin pohan STIKOM Tunas Bangsa

DOI:

https://doi.org/10.59934/jaiea.v1i2.74

Keywords:

Location, Datamining, K-Means Algorithm, Interests

Abstract

One of the strategies to increase sales in traditional markets is the strategy of placing the selling location. This is done so that the products marketed are in accordance with the type so that consumers will feel comfortable with the ease of shopping. In this study, observations were made on the traditional market of Horas market in the market service area of Pematangsiantar City. At this time the arrangement of selling locations has not been well organized so that there is little interest in the community to shop. This of course will affect the economic turnover of traders. These problems still occur today and there is no solution because market managers do not have a model that can be simulated. One of the computer science approaches to this problem is the K-Means algorithm data mining so that it is hoped that this research can help the market department in classifying merchandise locations in order to attract people's interest to shop at traditional markets so that there is an increase in the community's economy

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