Implementasi Metode Gabungan Multi-Factors High Order Fuzzy Time Series dan Fuzzy C-Means Untuk Peramalan Kebutuhan Energi Listrik di Indonesia - Sigit Pangestu; Dian Eka Ratnawati; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Indonesia is one of the countries consuming electricity which always experience the increasing need of electric energy every year. Electricity needs in the household sector from 2003 to 2013 in Indonesia increased by an average of 8% per year. While in the commercial sector the average increase of 10.1%. Growing demand for electrical energy should be properly handled in order to avoid the lack of electricity supply that can lead to inhibition of economic activity in Indonesia. Therefore it is needed a program that can help the supplier of electrical energy in Indonesia (PLN) to determine the amount of electrical energy that must be prepared. The Combined method Multi-Factors High Order Fuzzy Time Series and Fuzzy C-Means (FCM) can be used to forecast electrical energy requirements. Fuzzy C-Means replaces one of the processes in the Multi-Factors High Order Fuzzy Time Series method when creating subintervals. The path of the method is the determination of the Universe of Discourse, the determination of the number of clusters, the formation of subintervals with Fuzzy C-Means, the formation of fuzzy sets, the fuzzification process, the formation of Fuzzy Logic Relationship (FLR), and the defuzzification process. From the test results obtained the smallest MAPE (Mean Absolute Percentage Error) value of 1.7857%. MAPE results obtained that less than 10% indicate that Combined Methods Multi-Factors High Order Fuzzy Time Series and Fuzzy C-Means (FCM) is very good used to forecast electricity demand in Indonesia.