Kode Mata Kuliah | AK2283 / 3 SKS |
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Penyelenggara | 108 - Actuarial Science / FMIPA |
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Kategori | Lecture |
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| Bahasa Indonesia | English |
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Nama Mata Kuliah | Analisis Deret Waktu | Time Series Analysis |
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Bahan Kajian | - Pengenalan model deret waktu dan model regeresi linier
- Kestasioneran
- Model-model stasioner
- Model-model tak stasioner
- Identifikasi model
- Estimasi parameter menggunakan metode momen dan kuadrat terkecil
- Estimasi parameter menggunakan metode likelihood maksimum
- Uji diagnostik menggunakan analisis residual
- Prakiraan (forecasting) model ARIMA
- Batas prediksi prakiraan model ARIMA
- Model musiman (seasonal)
- Model deret waktu heteroscedasticity ARCH(1) dan GARCH(1) (pengayaan)
- Estimasi likelihood maksimum dan uji diagnostik model deret waktu heteroscedasticity (pengayaan)
| - Introduction to time series models and linear regression models
- Stationarity
- Stationary models
- Non-stationary models
- Model identification
- Parameter estimation uses the moment method and least
squares
- Parameter estimation uses the maximum likelihood method
- Diagnostic tests use residual analysis
- Forecast (forecasting) ARIMA models
- Prediction limits of ARIMA model forecasts
- Seasonal model (seasonal)
- Time series model heteroscedasticity ARCH(1) and GARCH(1) (enrichment)
- Maximum likelihood estimation and diagnostic testing of time series
modelsheteroscedasticity(enrichment)
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Capaian Pembelajaran Mata Kuliah (CPMK) | - Memiliki pengetahuan dan wawasan yang cukup tentang konsep deret waktu dan asumsi kestasioneran.
- Dapat mengidentifikasi model deret waktu stasioner dan non stasioner.
- Mampu menyelesaikan masalah berkaitan dengan penerapan model deret waktu ARIMA.
- Dapat menginterpretasikan prakiraan (forecasting) hasil model deret waktu.
| - Have sufficient knowledge and insight into the concept of time series and stationarity assumptions.
- Can identify stationary and non-stationary time series models.
- Able to solve problems related to the application of ARIMA time series models.
- Can interpret forecasts (forecasting) time series model results.
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Metode Pembelajaran | Ceramah dan diskusi | Lectures and discussions |
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Modalitas Pembelajaran | Bauran, Sinkron/asinkron, dan Mandiri/ Kelompok | Mixed, Synchronous/asynchronous, and Independent/Group |
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Jenis Nilai | ABCDE |
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Metode Penilaian | UTS, UAS, Kuis, Tugas & Praktikum. | Exam, Quiz, Assignment and Lab |
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Catatan Tambahan | Tidak ada | NA |
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