| dc.contributor.advisor | Budiarti, Retno | |
| dc.contributor.advisor | Septyanto, Fendy | |
| dc.contributor.author | Sitorus, Gishelle Jovanda | |
| dc.date.accessioned | 2023-10-02T06:33:36Z | |
| dc.date.available | 2023-10-02T06:33:36Z | |
| dc.date.issued | 2023 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/125728 | |
| dc.description.abstract | Minyak sawit merupakan komoditas perkebunan besar dengan jumlah produksi bulanan terbesar di Indonesia, serta Indonesia merupakan salah satu produsen minyak sawit terbesar di dunia. Oleh karena itu, penting untuk meramalkan jumlah produksi bulanan perkebunan besar minyak sawit. Penelitian ini bertujuan memprediksi jumlah produksi bulanan perkebunan besar minyak sawit di masa depan dengan menggunakan metode Seasonal Autoregressive Integrated Moving Average (SARIMA) dan Seasonal Autoregressive Integrated Moving Average dengan variabel eksogen (SARIMAX) dengan melibatkan nilai tukar rupiah terhadap USD. Data yang digunakan adalah data bulanan produksi perkebunan besar minyak kelapa sawit dari Januari 2009 - Desember 2018. Hasil penelitian menunjukkan bahwa nilai tukar rupiah terhadap USD sebagai variabel eksogen tidak memiliki pengaruh signifikan sehingga nilai Mean Absolute Percentage Error (MAPE) dari model SARIMA dan SARIMAX cenderung mirip. Berdasarkan evaluasi model, model SARIMAX memiliki performa yang lebih baik dibandingkan model SARIMA dengan nilai MAPE forecasting sebesar 6,82%. | id |
| dc.description.abstract | Crude palm oil is a large plantation commodity with the largest monthly production in Indonesia. Indonesia is also one of the largest palm oil producers in the world. Therefore, it is important to predict the monthly production volume of large palm oil plantations. This research is aimed at predicting the amount of monthly production of crude palm oil in the future by using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Seasonal Autoregressive Integrated Moving Average methods with exogenous variables (SARIMAX) by involving the rupiah exchange rate against the USD. The data used are data on the monthly production of crude palm oil from January 2009 - December 2018. The result shows that the exchange rate of the Rupiah against the USD as an exogenous variable has no significant impact, leading to similar Mean Absolute Percentage Error (MAPE) values for SARIMA and SARIMAX models. Based on model evaluation, SARIMAX outperforms SARIMA with a forecasted MAPE value of 6.82%. | id |
| dc.language.iso | id | id |
| dc.publisher | IPB University | id |
| dc.title | Peramalan Jumlah Produksi Minyak Sawit Menggunakan Metode SARIMA dan SARIMAX | id |
| dc.title.alternative | Forecasting the Amount of Palm Oil Production Using the SARIMA and SARIMAX Methods | id |
| dc.type | Undergraduate Thesis | id |
| dc.subject.keyword | plantation | id |
| dc.subject.keyword | crude palm oil | id |
| dc.subject.keyword | exchange rate | id |
| dc.subject.keyword | SARIMAX | id |
| dc.subject.keyword | SARIMA | id |
| dc.subject.keyword | forecasting | id |
