Utilization Of Data Mining To Classify The Locations Of New Street Food Businesses Attracted And Potentially Big Profits In The City Of Surakarta

Ismail Setiawan, Eko Purbiyanto
2020 Journal of Applied Engineering and Technological Science (JAETS)  
This study uses C4.5 algorithm to classify potentially large-profit businesses in the city of Surakarta. The data used are street vendors who are divided into 4 types of merchandise namely snacks, snacks, heavy foods and drinks. The locations that are targeted for classification are Car Free Day. The division of the Car Free Day zone was carried out to find out which areas had more influence on certain foods to get big profits. Car free day zone is divided into 4 parts, namely purwosari area -
more » ... y purwosari area - rumah makan diamond, rumah makan diamond - toko buku gramedia, toko buku gramedia - ngarsopuro and the last one is ngarsopuro – bundaran gladag. Based on the results of the study, the most profitable area to sell is the toko buku gramedia - ngarsopuro. Besides this research also classifies based on the ability of the production of raw materials, namely medium and large. The best business category that requires this type of medium-sized raw material is selling at the toko buku Gramedia - Ngarsopuro area, while for the best raw material the best area is the same among Purwosari - Rumah makan diamonds, Gramedia toko buku - Ngarsopuro and Ngarsopuro – bundaran gladak
doi:10.37385/jaets.v1i2.45 fatcat:vo3d4imfbjfwrhafreuxqod4wa