dc.identifier.citation | Akaike, H. (1973). Maximum likelihood identification of Gaussian autoregressive moving-average models. Biometrika, 60, 255-266. Ardebili, M., Hashemi, M., Shahabi, A., & Barough, M. (2015). Optimized selection of stock portfolio by using the fuzzy artificial neural networks web model, ARIMA & markowitz model in tehran stock exchange. European Online Journal of Natural and Social Sciences, 4(1), 831-844. Box, G., Jenkins, G., & Reinsel, G. (1994). Time Series Analysis, Forecasting and Control. Prentice-Hall, Englewood Cliffs, NJ. BPS. (2015). Data distribusi barang dengan menggunakan jasa kereta api untuk wilayah Jawa dan Sumatera. Chatfield, C. (2000). Time-Series Forecasting. New York: Chapman & Hall. Cowpertwait, P., & Metcalfe, A. (2009). Introductory Time Series with R. New York: Springer. Dickey, D., & Fuller, W. (1979). Distribution of the estimates for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74, 427--431. Holens, G. (1997). Forecasting and selling futures using ARIMA models and a neural network. ProQuest, (304378804). JPNN. (2015, April 27). Perkembangan Bisnis e-Commerce di Indonesia Melesat. Dipetik Januari 25, 2016, dari http://www.jpnn.com/read/2015/04/27/300672/Perkembangan-Bisnis-eCommerce-di-Indonesia-Melesat- KAI. (2016). Pelayanan Angkutan. Dipetik Januari 25, 2016, dari http://kargo.keretaapi.co.id/. Kominfo. (2016, Januari 22). Komitmen Kominfo Kembangkan e-Commerce. Dipetik Januari 25, 2016, dari http://kominfo.go.id/index.php/content/detail/6622/Komitmen+Kominfo+Kemba ngkan+%3Ci%3Ee-Commerce%3C-i%3E/0/berita_satker#.VqWcxlIavnI Ljung, G., & Box, G. (1978). On a measure of lack of time series models. Biometrika, 553-564. McLeod, A., & Li, W. (1983). Diagnostic checking ARMA timeseries models using squared residual autocorrelations. Journal of Time Series Analysis, 4, 269-273. Reza, R. M. (2015). Forecasting travel time and variations in travel time due to vehicle accidents in spatio-temporal context along freeway. ProQuest, (1752635231). Shabri, A., & Samsudin, R. (2014). Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis. The Scientific World Journal, doi:http://dx.doi.org/10.1155/2014/854520. Sterba, J., Rublíková, E., & y Ocerín, J. (2012). Hybrid ARIMA-neural network model for prediction of water consumption aggregate. Social Science Letters, 2(2), 1420. | in_ID |