Penerapan Metode Klasifikasi K-Nearest Neigbor pada Dataset Penderita Penyakit Diabetes
Abstract
Diabetes adalah penyakit yang berlangsung lama atau kronis serta ditandai dengan kadar gula (glukosa) darah yang tinggi atau di atas nilai normal. Jika diabetes tidak dikontrol dengan baik, Pengujian performa berbagai metode pada sebuah dataset merupakan salah satu cara dalam penetapan metode klasifikasi yang tepat, masalah yang diangkat pada penelitian ini adalah bagaimana mengukur performa metode klasifikasi dalam mengelola dataset penderita diabetes. Metode yang digunakan yaitu algoritma K-Nearest Neighbor (KNN), dimana merupakan sebuah metode untuk melakukan klasifikasi terhadap objek berdasarkan data pembelajaran yang jaraknya paling dekat dengan objek tersebut. Pada hasil akhir penelitian ini, telah dihitung akurasi tertinggi 39% pada K=3, presisi tertinggi 65% pada K=3 dan K=5, recall tertinggi 36% pada K=3, dan F-Measure tertinggi 46% pada K=3.
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