Implementasi Data Mining Menggunakan Model SVM untuk Prediksi Kepuasan Pengunjung Taman Tabebuya - Agus Darmawan; Nunu Kustian; Wanti Rahayu (Universitas Indraprasta PGRI Jakarta, 2018)
Park is an area built in hard and soft materials supporting each other and deliberately designed and created by people as an outdoor or indoor refreshment place. The Tabebuya Park in Jagakarsa, South Jakarta is a tourist attraction flocked by visitors on regular days and holidays. The place is very beautiful and can give a sensation different to the one in our daily activities. One of the ways to improve visitor’s satisfaction during their visit is by improving the park’s service quality. This research aims to predict the satisfaction of Tabebuya Park visitors by applying SVM (Support Vector Machine) algorithm method in which the experiments in the model are evaluated and validated using the Confusion Matrix and AUC (Area Under the Curve) with ROC (Receiver Operating Characteristic). From the results of the evaluation and validation, it can be concluded the average accuracy and performance of algorithm SVM is 86.00% with AUC value of 0.947.