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All Journal Jurnal Sosial Ekonomi Pertanian IJoICT (International Journal on Information and Communication Technology)
Agung Andiojaya
Badan Pusat Statistik
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Social Sciences

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TRANSMISI HARGA GABAH TERHADAP HARGA BERAS: TINJAUAN ARAH, BESARAN DAN LAMA PERUBAHAN Agung Andiojaya
JSEP (Journal of Social and Agricultural Economics) Vol 14 No 2 (2021): JURNAL SOSIAL EKONOMI PERTANIAN (J-SEP)
Publisher : University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jsep.v14i2.24304

Abstract

Policies to maintain rice prices are a sensitive policy in Indonesia so that the government controls the rice price tightly in every level of the rice market. To make sure it runs well, the government needs to take into account the magnitude, direction, and speed of transmission of the rice price changes. When these three things can be monitored and controlled well, the success rate of controlling prices is in hand. This study investigates the direction and speed of transmission of changes in grain prices at the farm level to changes in rice prices at various levels of trade. The empirical results utilizing Granger Causality Test and VAR indicate that changes in the price of grain at the farm level significantly cause changes in rice prices at the milling and wholesale levels in a unidirectional way. Meanwhile, there is a piece of additional information where changes in the retail price of rice significantly cause changes in the price of grain at the farm level rather than vice versa. By implementing the IRFs method reveal the transmission’s duration of price change takes place in the short term and long term. Considering these findings, the policy of stabilizing rice prices at the mill and wholesale levels should be implemented immediately when the price of farmers' grain begins to change.
Prediction and Simulation Spatio-Temporal Support Vector Regression for Nonlinear Data Khalilur Rahman; Margaretha Ari Anggorowati; Agung Andiojaya
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 1 (2020): June 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.61.477

Abstract

Spatio-temporal model forecasting method is a forecasting model that combines forecasting with a function of time and space.  This method is expected to be able to answer the challenge to produce more accurate and representative forecasting. Using the ability of method Support Vector Regression in dealing with data that is mostly patterned non-linear premises n adding a spatial element in the model of forecasting in the form of a model forecasting Spatio- Temporal. Some simulations have done with generating data that follows the Threshold Autoregressive model. The models are correlated into spatial points generated by several sampling methods. Simulation models are generated to comparing the accuracy between model Spatio-Temporal Support Vector Regression and model  ARIMA  based on  Mean  Error,  Mean Average Error, Root Mean Square Error, and Mean Average Percentage Error. Based on the evaluation results, it is shown that forecasting with the Spatio-Temporal Support Vector Regression model has better accuracy than forecasting ARIMA.
Co-Authors Khalilur Rahman Margaretha Ari Anggorowati