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Menentukan Source Terbaik Untuk Menemukan Pelanggan Potensial Menggunakan Algoritma K-Nearest Neighbor Irfan Mahendra; Putri Buana
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 1 No 1 (2020)
Publisher : Jurusan Teknologi Informasi - Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (749.718 KB) | DOI: 10.30630/jitsi.1.1.2


Increased competition in futures trading encourages companies involved in the futures trading business to more intensively capture customers' attention through advertising. PT Global Kapital Investama Berjangka or GK Invest currently uses advertising on several sources such as Facebook, Google, Instagram, and several other online advertising media as one of its marketing strategies. To avoid inefficiencies in advertising, an instrument that can assist companies in determining the most effective advertising media is needed. The K-Nearest Neighbor (KNN) algorithm is the most popular algorithm used for classifying objects. This algorithm is seen to be used to determine the best source for finding potential customers related to advertising. Based on the research results obtained the calculation of the accuracy of the K-Nearest Neighbor using the RapidMiner Application with the Cross Validation method with a K = 1 parameter of 99%.