@phdthesis{digilib59875,
           month = {May},
           title = {PENERAPAN METODE HYBRID AUTOREGRESSIVE INTEGRATED MOVING AVERAGE ? JARINGAN SARAF TIRUAN (ARTIFICIAL NEURAL NETWORK) BACKPROPAGATION UNTUK MEMPREDIKSI HARGA SAHAM},
          school = {UIN SUNAN KALIJAGA YOGYAKARTA},
          author = {NIM.: 19106010010 Dwi Wahyuni},
            year = {2023},
            note = {Pembimbing: M. Farhan Qudratullah, S.Si., M.Si.},
        keywords = {ARIMA; Forecasting; Stock Price; Hybrid ARIMA-ANN; saham syariah},
             url = {https://digilib.uin-suka.ac.id/id/eprint/59875/},
        abstract = {The Hybrid method is a method of combining two forecasting models used to improve forecasting accuracy. In this study, the ARIMA model will be combined with the ANN model. The ARIMA model is used to predict linear data, then the ANN model is used to model nonlinear data. this merging method will produce a Hybrid ARIMA-ANN model. The case study in this research is the weekly stock opening price of PT. Unilever Indonesia Tbk in January 2018 to December 2022. The results of this study, obtained the best ARIMA-ANN hybrid model (1,1,2)(4,3,1) with the proportion of training and testing data being 80:20. In the best model, the MSE value is 264868, and the MAPE value is 9.8\%. The ARIMA-ANN hybrid model has a smaller error value than the ARIMA model. The results of forecasting the stock price of PT Unilever Indonesia Tbk for the 209th week period amounted to 4467,401 to the 260th week period which amounted to 4448,148.}
}