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All Journal ESTIMASI: Journal of Statistics and Its Application ARRUS Journal of Mathematics and Applied Science
Kesuma, Ahmad Rizky
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Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Mathematics Physics

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Pemodelan Produk Domestik Regional Bruto (PDRB) di Indonesia Periode 2018-2021 dengan Analisis Regresi Data Panel Kesuma, Ahmad Rizky; Rinanda, Farikah Ayu; Astafira, Ilyas; Afriani, Nur; Fadlirhohim, Rizki Dwi; Lestari, Tri Septi Ayu; Sifriyani, Sifriyani
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.27522

Abstract

High and sustainable economic growth is the main condition or a must for the continuity of economic development and increased welfare. GRDP is defined as the total added value generated by all business units in an area. The analytical method used in this study is panel data regression analysis. Panel data regression is used to observe the relationship between one dependent variable and one or more independent variables. This study aims to determine the panel regression model of Gross Regional Domestic Product (GDP) in Indonesia for the period 2018 to 2021 and to find out whether the domestic investment investment variable and the cooperative business volume variable affect GRDP in Indonesia for the 2018-2021 period. The results obtained in this study are that the best panel regression model for modeling GRDP is the FEM model and the variable Domestic Investment Investment and Cooperative Business Volume are variables that have a significant effect on the GRDP variable in Indonesia for the 2018-2021 period.
Forecasting the Total of Paddy Production in Indonesia Using Time Series Regression Model Kesuma, Ahmad Rizky; Siringoringo, Meiliyani; Mahmuda, Siti
ARRUS Journal of Mathematics and Applied Science Vol. 4 No. 2 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience3175

Abstract

Time series regression (TSR) is a forecasting model that can be used when there are trend and seasonal patterns. Paddy is a source of rice, which is a staple food for the Indonesian people. Paddy has a seasonal pattern because its cultivation depends on the rainy season. This study forecasts the amount of paddy production in Indonesia based on monthly data of paddy production in Indonesia to determine the production of paddy in 2023 and to assess the ability of the TSR model to forecast paddy production. The results showed that paddy production in 2023 is forecasted to have the same seasonal pattern as in previous years and reaches its peak production in April at 8.699 million tons. The TSR model of paddy production has a mean absolute percentage error (MAPE) of 8.654% indicating a very good forecasting accuracy.
Co-Authors Afriani, Nur Astafira, Ilyas Fadlirhohim, Rizki Dwi Lestari, Tri Septi Ayu Mahmuda, Siti Rinanda, Farikah Ayu Sifriyani, Sifriyani Siringoringo, Meiliyani