PERAMALAN INFLASI DI INDONESIA MENGGUNAKAN METODE AUTOREGRESSIVE MOVING AVERAGE (ARMA)

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Authors

  • Cheryl Ayu Melyani Universitas Islam Indonesia
  • Atsila Nurtsabita Universitas Islam Indonesia
  • Ghaitsa Zahira Shafa Universitas Islam Indonesia
  • Edy Widodo Universitas Islam Indonesia

DOI:

https://doi.org/10.32665/james.v4i2.231

Keywords:

Inflasi, Peramalan, ARIMA, AIC, RMSE, Inflation, Prediction

Abstract

References

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Badan Pusat Statistik. ARIMA (Auto regressive Integrated Moving Average). diambil dari daps.bps.go.id: https://daps.bps.go.id/fileartike l/77/arima,pdf pada tanggal, 25 Mei 2021.

Fahrudin, R., & Sumitra, I. D. Peramalan Inflasi Menggunakan Metode SARIMA dan Single Exponential Smoothing (Studi Kasus: Kota Bandung). Majalah Ilmiah UNIKOM, (2020) 111-120.

Santoso, Teguh, & Kharisma, Bayu. Peramalan Inflas Kota Bandung dengan Pendekatan Box-Jenkins. Buletin Studi Ekonomi Vol.25 No.2, (2020).

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Silfiani, M., & Suhartono, Aplikasi Metode Ensembel untuk Peramalan Inflasi di Indonesia. Jurnal Sains Dan Seni ITS, (2012) 171-176.

Bustami, H, I., & Gamal, M, D., Holt-Winters Forecasting Method That Takes in to Account the Effect of Eid. Science Journal of Applied Mathematics and Statistics, (2015) 257-262.

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Tusyakdiah, H. Penerapan Metode Autoregressive Integrated Moving. diambil dari https://halimatusyak,medium,com/penera pan-metode-auto-regressive-integratedmoving -average-arima-pada-peramalan-harga-bitcoin-77558605eaf5 pada tanggal, 25 Mei 2021

Mulyana. Buku Ajar Analisis Deret Waktu. Universitas Padjajaran FMIPA Jurusan Statistika, Bandung, (2004).

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Wei, W. W. S. Time Series: Univariate and Multivariate Methods. Redwood City, Calif: Addison-Wesley. (1990).

Widarjono, A. Ekonometrikas Teori dan Aplikasi Untuk Ekonomi dan Bisnis. Ekonisia Fakultas Ekonomi Universitas Islam Indonesia. Yogyakarta. (2005).

As’ad, M., Wibowo, S, S., & Sophia, E. Peramalan Jumlah Mahasiswa Baru Dengan Model Autoregressive Integrated Moving Average (ARIMA), Jurnal Informatika Merdeka Pasuruan, (2017) Vol.2 No.3, 20-33,

Cort, W, J., & Kenji, M. Advantages of the Mean Absolute Error (MAE) Over the Root Mean Square Error (RMSE) in Assessing Average Model Performance. Department of Geography University of Delaware, Newark, (2005).

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Published

2021-10-31

How to Cite

[1]
C. A. Melyani, A. Nurtsabita, G. Z. Shafa, and E. Widodo, “PERAMALAN INFLASI DI INDONESIA MENGGUNAKAN METODE AUTOREGRESSIVE MOVING AVERAGE (ARMA)”, JaMES, vol. 4, no. 2, pp. 67–74, Oct. 2021.

Issue

Vol. 4 No. 2 (2021): Journal of Mathematics Education and Science

Section

Articles

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Abstract View: 945, PDF Download: 1063