Analisis Prediksi Jumlah Produksi Batu Bara Pt "B" Menggunakan Metode Arima-Garch Asimetris

Murdowati, Cahyaningtyas Rindhu (2022) Analisis Prediksi Jumlah Produksi Batu Bara Pt "B" Menggunakan Metode Arima-Garch Asimetris. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Batu bara memiliki peranan penting dalam pembangunan nasional. Produksi batu bara di Indonesia mengalami penurunan sebesar 53,63 juta ton pada tahun 2020 yang disebabkan oleh pandemi Covid-19, konsumsi batu bara turun, harga batu bara rendah, serta mobilitas karyawan perusahaan pertambangan dan logistik terbatas. Indonesia memiliki banyak produsen batu bara, salah satunya adalah PT “B”. Permintaan batu bara yang meningkat, produksi yang berusaha pulih akibat pandemi Covid-19, serta target produksi batu bara ditentukan berdasarkan permintaan dari departemen marketing. Namun, di PT “B” belum bisa memenuhi target produksi hariannya karena kendala operasi yang naik turun. Diperlukan analisis prediksi mengenai jumlah produksi batu bara untuk membantu perusahaan mempersiapkan permintaan batu bara di pasaran. Pada penelitian ini akan dilakukan analisis prediksi jumlah produksi batu bara khususnya actual coal getting PT “B” pada periode produksi harian pada Bulan Maret 2021 – Maret 2022 dengan metode ARIMA-GARCH Asimetris. Metode ARIMA dapat digunakan pada semua model data, data yang tidak stasioner, dan memiliki akurasi yang tinggi untuk prediksi jangka pendek. Sedangkan model GARCH dapat digunakan pada data yang memiliki varians yang tidak konstan atau heteroskedastisitas. Penggunaan model GARCH Asimetris seperti Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) dipilih karena mampu menangani adanya efek leverage atau asimetris pada volatilitas data. Berdasarkan hasil analisis, model terbaik yang diperoleh adalah ARIMA([1,6],1,[1,13,14])-EGARCH(1,1). Hasil penelitian menunjukkan bahwa model tersebut mampu menangkap pola data dengan baik dan menghasilkan nilai Mean Absolute Percentage Error (MAPE) yang kecil, sehingga akurat untuk digunakan sebagai alat prediksi. Hasil peramalan untuk tujuh periode mendatang menunjukkan bahwa jumlah produksi actual coal getting PT “B” cenderung stabil.
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Coal plays an important role in national development. Coal production in Indonesia decreased by 53.63 million tons in 2020 due to the Covid-19 pandemic, decreased coal consumption, low coal prices, and limited mobility of mining and logistics company employees. Indonesia has many coal producers, one of which is PT "B". Increasing demand for coal, production trying to recover from the Covid-19 pandemic, and coal production targets are determined based on demand from the marketing department. However, PT "B" has not been able to meet its daily production targets due to fluctuating operational constraints. A predictive analysis of the amount of coal production is needed to help the company prepare for coal demand in the market. In this study, a predictive analysis of the amount of coal production, specifically the actual coal getting of PT "B", will be carried out for the daily production period from March 2021 to March 2022 using the Asymmetric ARIMA-GARCH method. The ARIMA method can be used for all data models, non-stationary data, and has high accuracy for short-term predictions. Meanwhile, the GARCH model can be used for data that has non-constant variance or heteroscedasticity. The use of Asymmetric GARCH models such as Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) is chosen because it is able to handle the leverage or asymmetric effect on data volatility. Based on the analysis results, the best model obtained is ARIMA([1,6],1,[1,13,14])-EGARCH(1,1). The results show that the model is able to capture the data pattern well and produce a small Mean Absolute Percentage Error (MAPE) value, making it accurate for use as a prediction tool. The forecasting results for the next seven periods show that the actual coal getting production of PT "B" tends to be stable.

Item Type:	Thesis (Other)
Additional Information:	RSSt 519.535 Mur a-1 2022
Uncontrolled Keywords:	ARIMA. EGARCH. Coal Production. Forecasting. ARIMA. EGARCH. Produksi Batu Bara. Peramalan.
Subjects:	H Social Sciences > HA Statistics
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	10 Jun 2026 02:47
Last Modified:	10 Jun 2026 03:26
URI:	http://repository.its.ac.id/id/eprint/133676

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