OPTIMASI PERSEDIAAN MATERIAL TRANSFORMATOR MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN DAN ANT COLONY OPTIMIZATION DI PT. PLN (PERSERO) AREA JEMBER - Rizki Herdatullah; Syaiful Bukhori; Windi Eka Yulia Retnani (Faculty of Computer Science, University of Jember, 2019)
Optimization comes from basic words optimal which mean the best, highest, most beneficial, make the best, and do optimizing (make the best, highest, etc.). Forecasting is an attempt to predict the future. Prediction can be done by studying the pattern of historical data to find a model that can show future data. This methoed is called time series data forecasting. One of many algorithm that can builds model from historical data is Artificial Neural Networks (ANN). The algoritm mimics the human neuron system so that is can solve non-linear problems, such as the forecasting of transformator demand. In the process of modeling, ANN will always update the connection weights to find the optimum weights. In this final project ANN will be trained by Ant Colony Optimization (ACO). Based on the results can be seen that ANN with ACO as learning methods can predict transformator demand with good result.