ANALISIS VOLATILITAS HARGA KOMODITAS HORTIKULTURA STRATEGIS DI PROVINSI BENGKULU

Hariz Eko Wibowo, Ridha Rizki Novanda

Abstract

Economic growth was caused by unstable inflation which made it difficult for the public to carry out production, consumption and investment. Therefore, the purpose of this study is to analyze the level of volatility of strategic horticultural commodity prices in the Bengkulu Province which has an impact on inflation. The data used is monthly time series data for horticultural strategy commodity prices in Bengkulu Province from July 2017 to December 2022. The horticultural strategy commodities studied were shallots, red chilies and cayenne pepper. The data used is secondary data sourced from the National Strategic Food Price Information Center. Price volatility analysis uses a time series model with the help of R studio software. Forecast results using the ARIMA model for shallot prices, red chili prices, and cayenne pepper prices show relatively stable prices. The highest level of price volatility among horticultural commodity strategies in Bengkulu Province is red chili, followed by cayenne pepper, and then shallots. The volatility of the shallot price is 14.33%. Red chili price volatility is 20.83%. The price volatility of cayenne pepper is 18.66%. This shows that the volatility levels of shallot prices, red chili prices, and cayenne pepper prices are still under control and this is reinforced by the results that the model does not have an ARCH effect. Several anomalies such as prices that rose significantly in June 2022 were due to a decline in commodities due to farmers reducing the number of plants in line with high fertilizer prices, especially in Rejang Lebong Regency. This is also the impact of the post-pandemic.

Keywords

ARCH, GARCH, Inflation, Volatility

References

Dahoklory, D., Suryowati, K., Bekti, R.. D. 2016. Analisis Trend dan ARCH GARCH Untuk Meramalkan Jumlah Pasangan Usia Subur di Daerah Istimewa Yogyakarta. Jurnal Statistika Industri dan Komputasi. Vol 1(1):11-22

Engle R. 2001. The use of ARCH/GARCH models in applied econometrics. J Econ Perspect. 15:157- 168.

Hadiansyah, F. 2017. Prediksi Harga Cabai dengan Menggunakan pemodelan Time Series ARIMA. Indonesian Journal on Computing (Indo-JC), 2(1), 71. https://doi.org/10.21108/indojc.20 17.2.1.144

Irnawati, & Trisusanto, T. (2019). Peramalan Harga Eceran Cabai Merah Dengan Permodelan Time Series ARIMA. Jurnal Pilar Ketahanan Pangan, 01(02 Desember 2019), 39–48.

Joëts M, Mignon V, Razafindrabe T. 2017. Does the volatility of commodity prices reflect macro-economic uncertainty? Energy Econ [Internet]. [cited 2017 Oct 22]; 68:313-326. Available from: https://ac.els-cdn.com/S01409883 17303201/1-s2.0-S0140988317303201-main.pdf? _tid=3b40b63a-b79d-11e7-8189-00000aab0f26&acdnat=1508727341_cc20ad3daaf296bd2a7d200bad535517doi:10.1016/j.eneco.2017.09.017.

Makridakis, S. Weelwright , S.C. dan McGee, V.E. 1999. Metode dan Aplikasi Peramalan, Edisi Kedua, Terjemahan dari Forecasting, Second Edition, oleh U. S. Andriyanto dan A. Basith. Jakarta: Penerbit Erlangga

Mankiw, N., G. 2007. Makroekonomi. Surabaya: Erlangga.

Nugrahapsari, R., A., & Arsanti, I., W. 2018. Analisis Volatilitas Harga Cabai Keriting di Indonesia Dengan Pendekatan ARCH GARCH. Jurnal Agro Ekonomi Vol. 36 No. 1, Mei 2018:1-13.

Nurjati, E. 2021. Price Volatility of Red Chili Peppers In Central Java. Agrisosionomics 5(2): 152-167.

Pamungkas, M. B., & Wibowo, A. 2018. Aplikasi Metode ARIMA Box-Jenkins Untuk Meramalkan Kasus Dbd Di Provinsi Jawa Timur. The Indonesian Journal of Public Health, 13(2), 183. https://doi.org/10.20473/ijph.v13i 2.2018.183-196

[Pusdatin] Pusat Data dan Informasi Pertanian. 2016. Outlook komoditas pertanian sub sektor hortikultura: cabai merah. Jakarta (ID): Pusat Data dan Sistem Informasi Pertanian.

Rabbani, M., I. 2021. Pemodelan Harga Komoditi Kopi Arabika Menggunakan Pendekatan Model ARIMA-GARCH Asimetris. Institut Pertanian Bogor.

Sadiyah, F. 2021. Dampak Pandemi Covid-19 terhadap Pertumbuhan Ekonomi dan Perdagangan Komoditas Pertanian di Indonesia. Jurnal Ekonomi Pertanian Dan Agribisnis, 5(3), 950–961. https://doi.org/10.21776/ub.jepa.2021.005.03.30

Sukiyono, K., & Janah, M. 2019. Forecasting Model Selection of Curly Red Chili Price at Retail Level. Indonesian Journal of Agricultural Research, 2(1), 1–12. https://doi.org/10.32734/injar.v2i1 .859

Sumaryanto. 2009. Analisis volatilitas harga eceran beberapa komoditas pangan utama dengan model ARCH-GARCH. Jurnal Agroekonomi, Volume.27, No.2: 135-163. Oktober, ISSN (Online) 2541-1527

Windhy, A., M., & Jamil, A., S. 2021. Peramalan Harga Cabai Merah Indonesia: Pendekatan ARIMA. Jurnal Agriekstensia Vol. 20. No.1

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