Kristanto, Natasya Angelia and Mahanariswari, Luh Putu Ayu Eshanti (2024) Prediksi Nilai Tukar Rupiah Terhadap Dolar AS (Amerika Serikat) Menggunakan Model Autoregressive Moving Average (ARIMA). Project Report. [s.n.], [s.l.]. (Unpublished)
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Abstract
Laporan kerja praktik ini disusun sebagai bagian dari pemenuhan kurikulum Program Studi Sarjana Sains Aktuaria di Institut Teknologi Sepuluh Nopember. Penelitian ini bertujuan untuk memprediksi nilai tukar Rupiah terhadap Dolar Amerika Serikat (USD) menggunakan metode Autoregressive Integrated Moving Average (ARIMA), yang dikenal efektif untuk peramalan jangka pendek pada data deret waktu. Data yang digunakan merupakan kurs tengah harian Rupiah terhadap USD dari Januari 2023 hingga Agustus 2024 yang diperoleh dari laman resmi Bank Indonesia. Tahapan analisis dimulai dari statistika deskriptif, uji stasioneritas, transformasi Box-Cox, dan differencing, hingga pemodelan ARIMA. Model terbaik dipilih berdasarkan uji signifikansi parameter, uji diagnostik residual (white noise dan normalitas), serta nilai Akaike Information Criterion (AIC) terkecil. Hasil analisis menunjukkan bahwa model ARIMA (1,1,1) merupakan model paling optimal dalam menangkap pola fluktuasi nilai tukar, serta memberikan hasil peramalan yang cukup akurat. Temuan ini diharapkan dapat memberikan kontribusi dalam mendukung analisis kebijakan moneter serta manajemen risiko keuangan. Selain itu, pelaksanaan kerja praktik di Bank Indonesia memberikan mahasiswa pengalaman langsung mengenai dinamika pasar keuangan dan penerapan ilmu aktuaria dalam lingkungan profesional.
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This internship report is prepared as part of the academic requirements for the Bachelor's Program in Actuarial Science at Institut Teknologi Sepuluh Nopember. The study aims to forecast the exchange rate of the Indonesian Rupiah (IDR) against the United States Dollar (USD) using the Autoregressive Integrated Moving Average (ARIMA) method, which is widely recognized for its effectiveness in short-term time series forecasting. The data utilized consists of daily mid-market exchange rates of IDR to USD from January 2023 to August 2024, obtained from the official website of Bank Indonesia. The analytical steps include descriptive statistics, stationarity testing, Box-Cox transformation, differencing, and ARIMA modeling. The best model was selected based on the significance of parameters, residual diagnostic tests (white noise and normality), and the lowest Akaike Information Criterion (AIC) value. The results reveal that the ARIMA (1,1,1) model provides the most reliable forecast and effectively captures the exchange rate fluctuation patterns. These findings are expected to contribute to monetary policy analysis and financial risk management. Furthermore, the internship at Bank Indonesia has provided valuable hands-on experience and deeper insights into the practical application of actuarial science within the national financial sector.
| Item Type: | Monograph (Project Report) |
|---|---|
| Uncontrolled Keywords: | Nilai Tukar, Rupiah, Dolar AS, Deret Waktu, ARIMA, Peramalan, Aktuaria, Exchange Rate, Rupiah, USD, Time Series, ARIMA, Forecasting, Actuarial Science. |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HA Statistics > HA31.35 Analysis of variance H Social Sciences > HA Statistics > HA31.7 Estimation H Social Sciences > HG Finance > HG3881 Foreign exchange. |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Actuaria > 94203-(S1) Undergraduate Thesis |
| Depositing User: | Luh Putu Ayu Eshanti M. |
| Date Deposited: | 23 Jul 2025 06:18 |
| Last Modified: | 23 Jul 2025 06:18 |
| URI: | http://repository.its.ac.id/id/eprint/120842 |
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