Implementasi Algoritme Support Vector Regression Pada Prediksi Jumlah Pengunjung Pariwisata - Mimin Putri Raharyani; Rekyan Regasari Mardi Putri; Budi Darma Setiawan (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Tourism has an important role for the economic growth of a region. One of the factors affecting the tourism revenue sector is the number of visitors. The more number of visitors can increase revenue, if the number of visitors decreased it will have an impact on the development of tourist attractions that can harm the manager of tourism. The prediction system of the number of visitors is needed as an illustration of the level of the number of tourism visitors for the period to come and can provide information to the managers of tourism to prepare better facilities and infrastructure and able to manage income and expenses to minimize losses. The prediction of the number of visitors to tourism can be done by applying the Support vector regression algorithm. Support vector regression algorithm is a method that can solve regression problems and produce good performance in the solution. In this study data used 72 data on the number of visitors monthly on tourism from 2010 to 2015. Test results show that the average value of MAPE minimum generated is 9,16% and the best MAPE value obtained is 6,98% which means The average difference between the predicted result and the actual data is 115 visitor number with sigma parameter = 925,8409 lambda = 0,3868, cLR = 0,0802, epsilon = 1,27E-10, complexity = 3234,539, maximal iteration 5000.Keywords: prediction, tourism, visitor number, support vector regression