BibTex Citation Data :
@article{J.Gauss38012, author = {Nanda Lingkar Imani and Tarno Tarno and Bagus Saputra}, title = {PREDIKSI HARGA DAGING SAPI DI KABUPATEN BREBES MENGGUNAKAN PEMODELAN ARFIMA DENGAN EFEK GARCH}, journal = {Jurnal Gaussian}, volume = {12}, number = {4}, year = {2024}, keywords = {Beef; prediction; long memory; ARFIMA; GARCH.}, abstract = {Beef is a source of animal protein which is rich in nutrients and much-loved by the people of Indonesia. Brebes Regency is an area in Indonesia that has local livestock assets, namely Java Brebes cattle or also known as Jabres cattle. The existence of this jabres cattle is one of the guardians of beef price stability in Brebes in particular and in Central Java in general. The price of beef often fluctuates, to minimize losses, it is necessary to predict the market price. The model for predicting research data is the ARFIMA-GARCH model which is a model that can explain long memory patterns in time series data and experience heteroscedasticity problems. This study aims to obtain the best model with time series analysis and predict the selling price of beef in Brebes Regency for the next 52 weeks using ARFIMA modeling which is enhanced using the addition of the GARCH model. The results of the analysis that has been carried out on beef price data in Brebes Regency can be concluded that the best model obtained is the ARFIMA model ([9], 0.5461747, 0) – GARCH (1, 1). Based on the predictions that have been made using the best model, the resulting MAPE value is 1.56375%, so the model is very good for predicting beef prices in Brebes Regency in the next several periods.}, issn = {2339-2541}, pages = {570--580} doi = {10.14710/j.gauss.12.4.570-580}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/38012} }
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