KLASIFIKASI PENGUNJUNG WISATA DI KOTA PAGAR ALAM DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR (K-NN) - Syahri, Riduan; Puspita, Desi (Universitas PGRI Semarang, 2023)
The city of Pagar Alam has many beautiful tourist options, fresh and cold air, and unique culture and culinary delights. So that it becomes an area that is visited by many local and foreign tourists. Of the many visitors who come, not a few of them leave impressions in the form of reviews of the places they have visited. The purpose of this study is to determine the classification and to determine the accuracy produced by the K-Nearest Neighbor (K-NN) method. The K-Nearest Neighbor (K-NN) method is used to classify visitor data on Pagar Alam tours. Tests carried out to get good accuracy results and evaluate using a confusion matrix. This research produces a classification system that can identify and classify Pagar Alam tourism visitors using the K-Nearest Neighbor (K-NN) algorithm with the results obtained the greatest accuracy with a value of k = 3 with 99% accuracy, K0 gets 98% precision, recall 100 and a fi-score of 99%, for k1 precision 100%, the recal is 89% and the fi-score is 92%, while for K2 the precision is 100%, the recal is 100%, the f1-score is 100%.