Peramalan Tingkat Produksi Gula Menggunakan Multi Factor Fuzzy Time Series yang Dioptimasi dengan Algoritme Genetika - Kholifa'ul Khoirin; Budi Darma Setiawan; Agus Wahyu Widodo (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Sugar is one of the strategic commodities that affect the Indonesia's economy. This is because sugar is one of a essencial staple for Indonesian society. But on the other hand, the large demand of sugar consumption in Indonesian cannot meet with the low production of sugar. One of sugar factories is PG Candi Baru Sidoarjo. Besides production processing's factors, the factory is experiencing difficulties in its planning. Which in the production planning, the sugar factory will set targets that must to be achieved in future production. In an effort to overcome these problems, this study is expected to provide forecasting to see the possibility of achieving sugar production targets. Multi Factor Fuzzy Time Series method optimized with Genetic Algorithm by considering several factors influencing sugar production process such as number of milling days in one month, percentage of rendeman, and number of milled sugarcane. The genetic algorithm is used to perform subinterval optimization. Forecasting results of sugar production using a combination of these two methods get RMSE of 424,70. These results are smaller than the Multi Factor Fuzzy Time Series method without optimizing the subintervals that yield RMSE 6168,7437. Thus, it can be concluded that the proposed method is capable of forecasting better results than the unoptimized Multi Factor Fuzzy Time Series method.