Algoritma K-Means Untuk Clustering Rute Perjalanan Wisata Pada Agen Tour & Travel

Government support for the development of tourism has an impact on the growth of business opportunities for travel agents. Along with the advancement of the domestic travel sector, tour & travel agent business forms have sprung up that influence business competition between travel agents. The problem with tour & travel agents is the lack of information about tourist routes that are most in-demand by customers. To solve this problem the method used to classify the most desirable travel routes using the method of data mining is clustering with the K-Means algorithm. Based on the results of the study found three groups of travel routes, namely the most desirable travel routes by 20%, the trips that are in demand by 30% and less desirable trips by 50%.