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All Journal Prosiding Seminar Nasional Official Statistics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Parina, Okta
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Pemanfaatan Data Citra Satelit Untuk Memprediksi Produksi Padi Tahun 2018-2022 dengan Membandingkan Metode Machine Learning dan Ekonometrik Hidayat, Arief Ramadhan Rifky; Parina, Okta; Kurniawan, Robert
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1779

Abstract

This study aims to evaluate and compare the prediction accuracy of rice production in East Java in 2018-2022 using three methods namely Support Vector Regression (SVR), Autoregressive Integrated Moving Average With Exogenous Variable (ARIMAX), and Autoregressive Distributed Lag (ARDL). The dependent variable is rice production with the independent variables Normalized Difference Water Index (NDWI), Soil Adjusted Vegetation Index (SAVI), and Farmer's Exchange Rate (NTP) derived from satellite imagery and the Central Bureau of Statistics. The best model of this research is SVR with Radial Basis Function (RBF) because it has Mean Absolute Percentage Error (MAPE) and Mean Squared Error (MSE) values of 35.42% and 46.93. The parameters cost (C), gamma (γ), epsilon (ε), and number of support vectors used in the SVR model are 1; 0.33; 0.1; and 43. SAVI is the variable that best describes rice production because it has the same distribution pattern and is the only significant variable in the long-term model.
Unlocking Renewable Energy Potential: The Nexus Between Financial Inclusion and Renewable Energy in Indonesia Primasrani, Byun Jiye; Parina, Okta
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.733

Abstract

Indonesia has pledged to achieve net-zero emissions in 2060. The energy transition can be achieved through financial inclusion. Based on the Environmental Kuznets Curve (EKC) theory, financial inclusion can be a catalyst in reducing environmental impacts if a country has reached the EKC turning point. This study investigates the impact of financial inclusion on the consumption of renewable energy in Indonesia. The data used in this study will be the percentage of renewable energy consumption and the financial inclusion index from the International Monetary Fund 2004 to 2021. Additionally, economic growth and the number of internet users are included as control variables. This study utilizes the Error Correction Model and finds that financial inclusion and internet usage have a negative significant effect on the percentage of renewable energy consumption in the long run. Based on these findings, it can be concluded that according to EKC theory, Indonesia is still in an early stage of development, where increasing financial inclusion and technology still have a negative impact on the environment. Policymakers are encouraged to develop targeted financial inclusion strategies to enhance environmental sustainability. Green finance and green investment are critical solutions to support Indonesia's energy transition.
Co-Authors Hidayat, Arief Ramadhan Rifky Primasrani, Byun Jiye Robert Kurniawan, Robert