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All Journal Jurnal Pertanian Agros PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Swardanasuta, I Bagus Putu
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Agriculture, Biological Sciences & Forestry Computer Science & IT

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THE EFFECT OF INDUSTRIAL VALUE ADDED, ENERGY CONSUMPTION, FOOD CROP PRODUCTION, AND AIR TEMPERATURE ON GREENHOUSE GAS EMISSIONS IN INDONESIA: A TIME SERIES ANALYSIS APPROACH Swardanasuta, I Bagus Putu; Sandy, Nicholas Rahardian Kurnia; Rohmah, Nur Amaliyatur; Arindah, Yuli; Kartiasih, Fitri
Agros Journal of Agriculture Science Vol 26, No 1 (2024): Januari
Publisher : Fakultas Pertanian, Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jpa.v26i1.3876

Abstract

Air quality and global warming, which cause climate change and affect many aspects of human life, have become important topics in recent years. The objective of this study is to assess the influence of greenhouse gas emissions on industrial added value, energy consumption, food crop production, and air temperature in Indonesia. The period covered is 1990–2022. The Granger causality test and the vector error correction model are employed to establish the causal connection between the variables, and the unit root test is used to confirm the data’s stationarity. The study’s findings demonstrate that, over the long run, greenhouse gas emissions in Indonesia are known to be positively impacted by energy use, crop output, and temperature. Short-term analysis shows that air temperature has a negative impact on greenhouse gas emissions in Indonesia, but the added value of industry, energy consumption, and food crop output have a favorable impact. In light of the study’s findings, it is anticipated to serve as the foundation for the Indonesian government’s deliberations when implementing the required policies to lower greenhouse gas emissions, while still paying attention to the added value in the industrial sector as well as a basis for determining other policies. In addition, controlling fossil energy consumption must also be actively carried out by intensifying the use of renewable fuels. Keywords: Greenhouse gases, Industrial value added, Energy consumption, Food crop production, Air temperature, VECM
Forecasting Indonesian Monthly Rice Prices at Milling Level Using Google Trends and Official Statistics Data Swardanasuta, I Bagus Putu; Sofa, Wahyuni Andriana; Muchlisoh, Siti; Wijayanto, Arie Wahyu
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.v2025i1.521

Abstract

Hunger is a very complex social issue to address. Alleviating hunger is closely related to achieving food security, which is a goal in realizing the second Sustainable Development Goals (SDGs), zero hunger. The most frequently consumed food commodity by the Indonesian population is rice, which has fluctuating prices in the market. Therefore, price forecasting is necessary so that the government can take preventive measures against rice price increases at certain times. Research on rice price forecasting using big data from Google Trends is still very rare in Indonesia, even though Google Trends has great potential to reflect the public's search popularity for certain keywords. Therefore, this study aims to forecast the monthly medium rice price in Indonesia at the milling level using exogenous variables of dried milled grain prices and the popularity index of related keywords on Google Trends. The forecasting is conducted using Seasonal Autoregressive Integrated Moving Average (SARIMA), SARIMA with Exogenous Variables (SARIMAX), and Extreme Gradient Boosting (XGBoost) models. The SARIMAX model has the best performance in forecasting rice prices, with a Root Mean Squared Error (RMSE) of 941.6933, Mean Absolute Error (MAE) of 817.9021, and Mean Absolute Percentage Error (MAPE) of 0.0620.
Co-Authors Arie Wahyu Wijayanto Arindah, Yuli Fitri Kartiasih Muchlisoh, Siti Rohmah, Nur Amaliyatur Sandy, Nicholas Rahardian Kurnia Sofa, Wahyuni Andriana