Optimasi SVR dengan Ant Colony Optimization untuk Prediksi Tingkat Produksi Susu Segar (Studi Kasus pada Koperasi Susu SAE Pujon, Malang) - Karuniawan Susanto; Rekyan Regasari Mardi Putri; Sutrisno Sutrisno (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Milk is a food of livestock that has a complete and balanced nutrition where its protein nutrition is higher than vegetable protein. The consumption of milk and its products play a role in improving the quality of human resources in Indonesia that is still low. Therefore, the role of milk manufacture industry in Indonesia is very important in terms of providing and sufficient nutrition needs of the people. One of the milk manufacture industry is dairy cooperatives of SAE Pujon, Malang. In order to be able to play a role well, the production rates of fresh milk in dairy cooperatives of SAE Pujon is important things that need to be optimized. Improper production rates will result in losses, such as loss in the form of material or loss of consumers. Based on these problems, it takes support vector regression method optimized with ant colony optimization that is implemented into a system. Optimization is done to determine the most optimal SVR parameter. The optimized SVR parameter are (sigma), C (complexity), (epsilon), cLR (learning rate constants) and (lambda). Range of ACO parameter values to obtain optimal SVR parameter value is q0 = 0,5-1, Î± = 0,01-0,04, = 0,01-0,04, Ï = 0,001-0,004, Î´ = 0,001-0.004. The milk production rates forecasting in dairy cooperatives of SAE Pujon from January until December 2016 by using SVR-ACO resulted MAPE value of 3,30425%.