Rifa'i Anwar Primary Author mixed material bibliography Bandung Maranatha University Press 2020 Indonesia

Artikel Jurnal

hlm : 234-241 Abstract Crude Palm Oil (CPO) is one of Indonesia's best export commodities. CPO production competition causes price fluctuations so that it can trigger losses. The solution that can be taken to avoid losses is to predict the price of CPO. Time series data in the previous months, starting from January 2009 until January 2020, are used as a reference to predict the next CPO price. In this research, CPO price prediction is carried out with a combination of artificial intelligence concepts, namely Radial Basis Function Neural Network (RBFNN), and fuzzy logic. The combination of these methods, namely Fuzzy Radial Basis Function Neural Network (FRBFNN), is then optimized using genetic algorithms. The prediction results show that the error based on the MAPE value for FRBFNN prediction on training data is 11.7% and the MAPE value for testing data is 9.4%. In the FRBFNN prediction that was optimized using a genetic algorithm, the MAPE value was 10.2% for training data and 8.3% for testing data. Informatika Sistem Informasi JUTISI 24432210 Perpustakaan Teknik UPI YAI JUTISI V6N2 Agustus 2020 JUTISI2-008 Perpustakaan FT UPI YAI JUTISI V6N2 Agustus 2020 cover_issue_174_en_US.png.png 59203 2023-02-22 14:12:08 2023-02-22 14:12:08 machine generated