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All Journal Dynamic Management Journal Prosiding Seminar Nasional Official Statistics
Hidayat, Anang Kurnia
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Other

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SELECTING THE BEST MODEL FOR FORECASTING INDONESIA'S OIL AND GAS IMPORT VALUE USING ARIMAX AND ARIMAX-LSTM Zega, Alvandi Syukur Rahmat; Hidayat, Anang Kurnia; Jannah, Nazwa Thoriqul; Kartiasih, Fitri
Dynamic Management Journal Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/dmj.v8i4.10776

Abstract

In order for the government to make the best policy decisions going forward, it is critical to forecast the value of oil and gas imports. This study aims to anticipate Indonesia's oil and gas import value by taking into account the independent variables of inflation, rupiah exchange rates, and global crude oil prices. The ARIMA (Autoregressive Integrated Moving Average), ARIMAX (ARIMA With Exogenous Variable), and Hybrid ARIMAX-LSTM (ARIMA With Exogenous Variable Long-Short-Term Memory) are the methods that are compared. Mean Absolute Percentage Error, or MAPE, is a tool used to compare forecasting models. The outcomes demonstrated how well ARIMAX-LSTM (0, 1, 2) predicts and forecasts the value of oil and gas imports when combined with variables for inflation and crude oil prices. According to the forecasting results, the value of imports of gas and oil increased by 3.03% between January and September of 2024 when compared to the entire import value of the year prior (Y-o-Y). Other exogenous variable addition, additional research on hyperparameter tuning, and the use of cross-validation techniques to increase prediction accuracy and provide more precise measurements of model performance are other recommendations for future investigation.
Peramalan Volume Timbulan Sampah dengan Memanfaatkan Indeks Google Trends Menggunakan Metode SARIMAX Hidayat, Anang Kurnia; Wijayanto, Arie Wahyu
Seminar Nasional Official Statistics Vol 2025 No 1 (2025): Seminar Nasional Official Statistics 2025
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2025i1.2514

Abstract

In recent years, the Special Region of Yogyakarta has faced a growing challenge of waste generation exceeding its management capacity. This situation underscores the urgency of developing a long-term, data-driven waste management strategy. This study aims to build an accurate forecasting model for waste volume using real-time data from the Google Trends Index (GTI) alongside official statistical data as exogenous variables. The forecasting methods employed are SARIMA and SARIMAX, tested with various parameter and variable combinations. The best-performing model is SARIMAX(1,1,1)(1,0,0)12 with the Production Index (IBS) and the GTI for the keyword “sampah” (waste) as exogenous variables, achieving a MAPE of 5.7873 (classified as very good) and an RMSE of 46.7509. The forecast shows an upward trend in mid-2024, a decline at the end of 2024, and a sharp increase in early 2025. These results can inform adaptive waste management policies, particularly in strengthening upstream strategies such as waste reduction, sorting, and recycling.
Co-Authors Arie Wahyu Wijayanto Fitri Kartiasih Jannah, Nazwa Thoriqul Zega, Alvandi Syukur Rahmat