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Pemodelan Generalized Space Time Autoregressive untuk Meramalkan Indeks Harga Konsumen

Authors

  • Agnesya Risnandar Statistika, Universitas Islam Bandung
  • Anneke Iswani Achmad

DOI:

https://doi.org/10.29313/jrs.v3i1.1792

Keywords:

Generalized Space Time Autoregressive, RMSE, Indeks Harga Konsumen

Abstract

Abstract. Inflation is an economic problem that often arises in Indonesia. Inflation is a continuous increase in the price of goods and services which can cause a decrease in the value of money. Inflation plays an important role in determining economic conditions, one of the indicators used to measure the inflation rate is the Consumer Price Index (CPI). The CPI is not only influenced by the previous time element, but also influenced by the inter-location element. The Generalized Space Time Autoregressive (GSTAR) method is one of the methods that can be used to analyze data that involves the relationship between time and location. This research will use CPI data for 7 cities in West Java, namely Bogor City, Sukabumi City, Bandung City, Cirebon City, Bekasi City, Depok City, and Tasikmalaya City with monthly period data from January 2014 to December 2019. This study aims to obtain the best GSTAR model and forecasting results for CPI data for 7 cities in West Java. Based on the research results, the GSTAR (5.1)I(1) model with uniform weights has the smallest RMSE value of 0.467767 compared to the distance inverse weight and cross-correlation normalization, so the best model for CPI data for 7 cities in West Java is the GSTAR (5.1)I(1) model with uniform weight. The forecasting results obtained, in general, in 2023 the CPI of 7 cities in West Java will experience a periodic increase.

Abstrak. Inflasi merupakan permasalahan ekonomi yang sering muncul di Indonesia. Inflasi adalah kenaikan harga barang dan jasa secara terus menerus yang dapat menyebabkan penurunan nilai uang. Inflasi berperan penting dalam menentukan kondisi perekonomian, salah satu indikator yang digunakan untuk mengukur tingkat inflasi adalah Indeks Harga Konsumen (IHK). IHK tidak hanya dipengaruhi oleh unsur waktu sebelumnya, tetapi juga dipengaruhi oleh unsur antar lokasi. Metode Generalized Space Time Autoregressive (GSTAR) merupakan salah satu metode yang dapat digunakan untuk menganalisis data yang melibatkan keterkaitan antar waktu dan lokasi. Pada penelitian ini akan digunakan data IHK 7 kota di Jawa Barat yaitu Kota Bogor, Kota Sukabumi, Kota Bandung, Kota Cirebon, Kota Bekasi, Kota Depok, dan Kota Tasikmalaya dengan data periode bulanan dari Januari 2014 sampai Desember 2019. Penelitian ini bertujuan untuk mendapatkan model GSTAR terbaik dan hasil peramalan untuk data IHK 7 kota di Jawa Barat. Berdasarkan hasil penelitian model GSTAR (5,1)I(1) dengan bobot seragam memiliki nilai RMSE terkecil yaitu sebesar 0.467767 dibandingkan dengan bobot invers jarak dan normalisasi korelasi silang, sehingga model terbaik untuk data IHK 7 kota di Jawa Barat yaitu model GSTAR (5,1)I(1) dengan bobot seragam. Hasil peramalan yang diperoleh, secara umum pada tahun 2023 IHK 7 kota di Jawa Barat mengalami peningkatan secara periodik.

References

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P. E. Pfeifer and S. J. Deutsch, “Identification and Interpretation of First Order Space-Time ARMA Models,” Technometrics, vol. 22, no. 3, pp. 397–408, Aug. 1980, doi: 10.2307/1268325.

S. Borovkova, H. P. Lopuhaä, and B. N. Ruchjana, “Consistency and asymptotic normality of least squares estimators in generalized STAR models,” Stat Neerl, vol. 62, no. 4, pp. 482–508, Nov. 2008, doi: 10.1111/j.1467-9574.2008.00391.x.

G. P. D. Sohibien, “Perbandingan Model STAR dan GSTAR Untuk Peramalan Inflasi Dumai, Pekanbaru, Dan Batam,” Jurnal Statistika Universitas Muhammadiyah Semarang, vol. 5, no. 1, pp. 14–26, 2017.

A. Dardiri, Indeks Harga Konsumen 8 Kota di Provinsi Jawa Timur 2018. Jawa Timur: BPS Provinsi Jawa Timur, 2018.

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Published

2023-07-16