
OPTIMASI PERSEDIAAN MATERIAL TRANSFORMATOR MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN DAN ANT COLONY OPTIMIZATION DI PT. PLN (PERSERO) AREA JEMBER
Author(s) -
Rizki Herdatullah,
Syaiful Bukhori,
Endah Yulia
Publication year - 2019
Publication title -
informal
Language(s) - English
Resource type - Journals
ISSN - 2503-250X
DOI - 10.19184/isj.v4i1.12892
Subject(s) - ant colony optimization algorithms , computer science , artificial neural network , ant colony , artificial intelligence , mathematical optimization , mathematics
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.