Aminnudin, Yoga Faisal (2018) Penerapan Filter Kalman dalam Perbaikan Hasil Prediksi Return Harga Minyak Mentah Dunia dengan Model ARIMA. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Peramalan terhadap harga komoditas minyak mentah dunia merupakan salah satu studi yang dilakukan untuk mengantisipasi harga periode mendatang dari komoditas minyak guna menjaga kestabilan ekonomi. Pada penelitian ini digunakan Autoregressive Integrated Moving Average dan Generalized Autoregressive Conditional Heteroscedastic (ARIMA) untuk merumuskan model peramalan return harga komoditas minyak mentah. Pada ARIMA didapatkan model yang sesuai yaitu ARIMA ([14],0,[14]) dengan nilai Mean Absolute Percentage Error (MAPE) yang masih sangat besar yaitu 217,2554%.Setelah didapatkan model yang sesuai dilakukan estimasi terhadap parameter dan perbaikan error pada model tersebut dengan Filter Kalman.
Hasil akhir menunjukkan bahwa model peramalan pada return harga minyak terbaik adalah dari hasil perbaikan error menggunakan Filter Kalman yang memiliki nilai MAPE terkecil yaitu 3,6947% sehingga hasil ramalan lebih akurat.
================================================================================================================== A forecasting of world crude oil commodity prices is one of several studies to anticipate the upcoming price of crude oil to maintain the economic stability. In this research, Autoregressive Integrated Moving Average (ARIMA) were used to formulate the
return forecasting model of crude oil prices.
ARIMA model gave the appropriate model of ARIMA ([14],0,[14]) with a large Mean Absolute Percentage Error (MAPE) value of 217. 2554%. Once the appropriate model has been obtained, therefore parameter estimation and error correction on the model were conducted by using Filter Kalman. The final result showed that the best
return forecasting of oil prices model was given by the error correction result using Filter Kalman model with the smallest MAPE value of 3.6947%, so the forecast result was
more accurate and close to the real ones.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSMa 519.2 Ami p |
| Uncontrolled Keywords: | ARIMA; Estimasi Parameter; Filter Kalman; Perbaikan Error; Error Correction; Parameter Estimation |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models. H Social Sciences > HF Commerce H Social Sciences > HG Finance > HG4529 Investment analysis Q Science > QA Mathematics Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA402.3 Kalman filtering. |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Aminnudin Yoga Faisal |
| Date Deposited: | 08 May 2018 04:24 |
| Last Modified: | 18 Jun 2020 04:38 |
| URI: | http://repository.its.ac.id/id/eprint/51300 |
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