Peramalan Rata – Rata Harga Beras Menggunakan Metode Vector Autoregressive (Var)

Djorgi, Andreas (2021) Peramalan Rata – Rata Harga Beras Menggunakan Metode Vector Autoregressive (Var). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kebutuhan beras setiap tahun semakin meningkat terutama pada wilayah yang padat penduduk. Kota Sidoarjo, Surabaya, dan Gresik termasuk wilayah yang padat penduduk di Provinsi Jawa Timur dan lokasinya berdekatan. Kenaikan harga beras di satu lokasi diduga menyebabkan kenaikan harga beras di lokasi lain yang berdekatan. Perusahaan Umum BULOG (Badan Urusan Logistik) adalah perusahaan yang bertanggung jawab dalam melakukan stabilisasi harga beras ketika mengalami kenaikan yang tidak wajar. Oleh karena itu diperlukan suatu peramalan harga beras agar dapat digunakan oleh BULOG untuk mengantisipasi adanya kenaikan harga beras. Pada penelitian ini dilakukan peramalan rata-rata harga beras di Kota Gresik, Sidoarjo, dan Surabaya pada periode yang akan datang menggunakan metode Vector Autoregressive (VAR). Hasil penelitian ini menunjukkan bahwa model peramalan terbaik untuk lokasi Sidoarjo dan Gresik adalah VARI ([1,2,3,4,5,6,10],1) yang artinya harga beras di Sidoarjo dipengaruhi oleh harga beras di Sidoarjo sendiri pada 1 dan 2 bulan sebelumnya, serta dipengaruhi oleh harga beras di Gresik pada 4, 5, dan 6 bulan sebelumnya. Model peramalan terbaik Lokasi Surabaya adalah VARI ([2,3,5,7,10,12],1) yang artinya harga beras di Surabaya dipengaruhi oleh harga beras di Surabaya sendiri pada 1 bulan sebelumnya. Harga beras di Surabaya juga dipengaruhi oleh harga beras di Sidoarjo pada 2, 3, 4, dan 6 bulan sebelumnya, serta dipengaruhi oleh harga beras di Gresik pada 10 dan 11 bulan sebelumnya, selain itu Harga beras di Gresik dipengaruhi oleh harga beras di Gresik sendiri pada 1 bulan sebelumnya.
Kata Kunci: Beras, BULOG, penduduk, peramalan, VAR.  
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The need for rice every year is increasing, especially in densely populated areas. Sidoarjo, Surabaya, and Gresik are among the densely populated areas in East Java Province and are located nearby. The increase in the price of rice in one location is thought to cause a rise in the price of rice in another nearby location. Bulog General Company (Logistics Agency) is a company responsible for stabilizing rice prices when it experiences an unnatural increase. Therefore, it is necessary to forecast the price of rice in order to be used by BULOG to anticipate the increase in rice prices. In this study, the average price of rice in Gresik, Sidoarjo, and Surabaya in the coming period was conducted using Vector Autoregressive (VAR) method. The results of this study showed that the best forecasting model for Sidoarjo dan Gresik location is VARI ([1,2,3,4,5,6,10,14],1) which is influenced by the price of rice in Sidoarjo itself in the 1 and 2 previous month, and influenced by the price of rice in Gresik in the previous 4, 5, and 6 months. The best forecasting model for Surabaya and Gresik is VARI ([2,3,5,7,10,12],1) which means that the price of rice in Surabaya is influenced by the price of rice in Surabaya itself in the previous month. Rice prices in Surabaya were also influenced by rice prices in Sidoarjo in the previous 2, 3, 4, and 6 months, and were influenced by rice prices in Gresik in the previous 10, and 11 months. in addition, the price of rice in Gresik was influenced by the price of rice in Gresik itself in the previous month. The results of this forecast can provide information to Perum BULOG to stabilise rice prices in Sidoarjo, Surabaya, and Gresik in 2021.
Keywords: BULOG, Forecasting, Rice, Population, VAR

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Beras, BULOG, penduduk, peramalan, VAR, BULOG, Forecasting, Rice, Population, VAR
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics
Depositing User:	ANDREAS DJORGI
Date Deposited:	14 Aug 2021 04:16
Last Modified:	14 Aug 2021 04:16
URI:	http://repository.its.ac.id/id/eprint/86132

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