Developing Panel Data and Time Series Application (DELTA) : Smoothing Module
DOI:
https://doi.org/10.34123/jurnalasks.v8i2.51Keywords:
smoothing, forecasting, time series application, panel data application, exponential, moving averageAbstract
Smoothing is commonly used methods to predict time series data. There are many applications that help in the processing of time series data that provide smoothing function such as EViews, Minitab, Zaitun TS, and R. However, these applications have some shortcomings such as the difficulty in comparing several methods. In this study, we build an open source application that provides more complete smoothing method and a facility for comparing several methods, namely smoothing module in DELTA application. Based on the tests, it can be proved that this application is suitable for users and the displayed output is consistent with the theory.
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References
J. L. Whitten and L. D. Bentley, System Analysis & Design Methods, New York: McGraw-Hill, 2007.
M. A. Weisfeld, The Object-Oriented Thought Process, Third Edition, USA: Addison-Wesley Professional, 2009.
R. S. Pressman, Software Engineering : A Practicioner's Approach, Seventh Edition, New York: McGraw-Hill, 2010.
J. P. Mueller, Beginning Programming with Python For Dummies, New Jersey: John Wiley and Sons, 2014.
D. C. Montgomery, L. A. Johnson and J. S. Gardiner, Forecasting & Time Series Analysis 2nd Edition, Singapore: McGraw-Hill, 1990.
S. G. Makridakis, S. C. Wheelwright and R. J. Hyndman, Forecasting : Methods and Applications, Chichester: John Wiley and Sons, 1997.
B. Abraham and J. Ledolter, Statistical Methods for Forecasting, New Jersey: Wiley-Interscience, 1983.
Usability.gov, "System Usability Scale (SUS)," [Online]. Available: https://www.usability.gov/how-to-and-tools/methods/system-usability-scale.html. [Accessed 6 7 2017].
Python Software Foundation, "Python," [Online]. Available: https://www.python.org. [Accessed 10 Januari 2017].
P. J. Brockwell and R. A. Davis, Introduction to Time Series and Forecasting, New York: Springer, 2002.
G. E. Bo, G. M. Jenkins and G. C. Reinsel, Time Series Analysis Forecasting and Control 3rd Edition, USA: Prentice-Hall, 1994.
B. Juanda and J. , Ekonometrika Deret Waktu, Bogor: IPB Press, 2012.
A. M. Sholihah, "Perancangan dan Implementasi Program Aplikasi Time Series dengan Metode Pemulusan dan Dekomposisi Untuk Peramalan," Jakarta, 2007.
N. E. Oktafiani and F. Andriyani, "Aplikasi Pemulusan Eksponensial dari Brown dan dari Holt Untuk Data Yang Memuat Trend," in Seminar Nasional Aplikasi Sains & Teknologi (SNAST) Periode III, 2012.
Yuniastari, N. L. A. Kartika and I. W. W. Wirawan, "Peramalan Permintaan Produk Perak Menggunakan Metode Simple Moving Average dan Exponential Smoothing," Jurnal Sistem dan Informatika Vol.9, pp. 97-106, 2014.
M. A. Weisfeld, The Object-Oriented Thought Process, Third Edition, USA: Addison-Wesley Professional, 2009.
R. S. Pressman, Software Engineering : A Practicioner's Approach, Seventh Edition, New York: McGraw-Hill, 2010.
J. P. Mueller, Beginning Programming with Python For Dummies, New Jersey: John Wiley and Sons, 2014.
D. C. Montgomery, L. A. Johnson and J. S. Gardiner, Forecasting & Time Series Analysis 2nd Edition, Singapore: McGraw-Hill, 1990.
S. G. Makridakis, S. C. Wheelwright and R. J. Hyndman, Forecasting : Methods and Applications, Chichester: John Wiley and Sons, 1997.
B. Abraham and J. Ledolter, Statistical Methods for Forecasting, New Jersey: Wiley-Interscience, 1983.
Usability.gov, "System Usability Scale (SUS)," [Online]. Available: https://www.usability.gov/how-to-and-tools/methods/system-usability-scale.html. [Accessed 6 7 2017].
Python Software Foundation, "Python," [Online]. Available: https://www.python.org. [Accessed 10 Januari 2017].
P. J. Brockwell and R. A. Davis, Introduction to Time Series and Forecasting, New York: Springer, 2002.
G. E. Bo, G. M. Jenkins and G. C. Reinsel, Time Series Analysis Forecasting and Control 3rd Edition, USA: Prentice-Hall, 1994.
B. Juanda and J. , Ekonometrika Deret Waktu, Bogor: IPB Press, 2012.
A. M. Sholihah, "Perancangan dan Implementasi Program Aplikasi Time Series dengan Metode Pemulusan dan Dekomposisi Untuk Peramalan," Jakarta, 2007.
N. E. Oktafiani and F. Andriyani, "Aplikasi Pemulusan Eksponensial dari Brown dan dari Holt Untuk Data Yang Memuat Trend," in Seminar Nasional Aplikasi Sains & Teknologi (SNAST) Periode III, 2012.
Yuniastari, N. L. A. Kartika and I. W. W. Wirawan, "Peramalan Permintaan Produk Perak Menggunakan Metode Simple Moving Average dan Exponential Smoothing," Jurnal Sistem dan Informatika Vol.9, pp. 97-106, 2014.
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Published
2016-12-31
How to Cite
mariyah, siti, & Deli, N. F. (2016). Developing Panel Data and Time Series Application (DELTA) : Smoothing Module. Jurnal Aplikasi Statistika & Komputasi Statistik, 8(2), 14. https://doi.org/10.34123/jurnalasks.v8i2.51
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