Sari, Hanna Kartika (2015) Peramalan Arus Uang Harian Di kantor Pusat Bank Indonesia Untuk Perencanaan Peredaran Uang Kartal Dengan Metode Regresi Time Series Dan ARIMAX Variasi Kalender - Forecasting Of Daily Cash Flow In Bank Indonesia For Planning Currency Circulation Using Time Series Regression And Calender Variation Arimax Method. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
Preview |
Text
1313105006-Undergraduate Thesis.pdf - Published Version Download (3MB) | Preview |
Preview |
Text
1313105006-Paper.pdf - Published Version Download (586kB) | Preview |
Preview |
Text
1313105006-Presentation.pdf - Published Version Download (2MB) | Preview |
Abstract
Bank Indonesia merupakan otoritas moneter yang mempunyai tugas
menetapkan dan melaksanakan kebijakan moneter, dengan mengendalikan
jumlah uang beredar. Ketersediaan uang rupiah layak edar tercermin oleh
jumlah dan laju pertumbuhan uang kartal yang diedarkan (UYD) maupun
aliran uang kartal yang keluar dari Bank Indonesia ke perbankan dan
masyarakat (outflow) dan aliran uang kartal yang masuk melalui Bank
Indonesia (inflow). Kebutuhan uang kartal di Indonesia cenderung meningkat
di hari tertentu seperti hari raya Idul Fitri. Sehingga jauh-jauh hari Bank
Indonesia mengantisipasi hal tersebut dengan cara meramalkan. Pada penelitian
ini dilakukan peramalan arus uang harian di Kantor Pusat Bank
Indonesia dengan metode Regresi Time Series serta ARIMAX Variasi
Kalender Multi Input dan Single Input. Data yang digunakan adalah data
inflow dan outflow harian serta dummy variasi kalender. Hasil analisis menunjukkan
bahwa rata-rata inflow uang kartal cenderung meningkat pada
hari Selasa dan Rabu, Minggu kedua, bulan Agustus. Sedangkan outflow
meningkat pada Kamis dan Jum’at, Minggu keempat, bulan Juli. Metode
regresi time series merupakan metode terbaik untuk meramalkan inflow dan
outflow. Berdasarkan hasil RMSE terkecil yang dibandingkan dengan ketiga
metode, didapatkan model 1 regresi time series baik untuk meramalkan
inflow 2015 sedangkan model 3 regresi time series baik untuk meramalkan
outflow 2015. Hal ini menunjukkan bahwa model yang komplek tidak selalu
menghasilkan ramalan yang lebih akurat dibanding model yang sederhana.
========================================================================================================================
Bank Indonesia is the monetary authority has the task that define
and implement monetary policy by controlling the money supply.
Availability of money circulation is reflected by the amount and rate of
growth of currency in circulation (UYD) as well as the flow of currency
out of a Bank Indonesia to banks and the public (outflow) and the flow
of currency that goes through Bank Indonesia (inflow). The need for
currency in Indonesia tends to increase at certain days such as Eid. So
far the Bank Indonesia anticipate this by way of predicting. In this
research, did forecasting daily cash flow at Head Office of Bank
Indonesia using Time Series Regression and Calendar Variation
ARIMAX Multi Input and Single Input. Data for this research is daily
inflow and outflow and calendar variations dummy. The result of
analysis showed that the average inflow of currency tends to rise on
Tuesday and Wednesday, the second week, the month of August. While
outflows increased on Thursday and Friday, the fourth Sunday in July.
Time series regression method is the best method to forecast the inflow
and outflow. Based on the results of the smallest RMSE compared with
the three methods, it was found 1 time series regression models to
predict both inflow in 2015 while three time series regression models to
predict both outflow 2015. This indicates that the model is complex does
not always produce more accurate predictions than the simple model.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 511.526 Sar p |
| Uncontrolled Keywords: | ARIMAX Variasi Kalender, Inflow, Outflow, Regresi Time Series, Uang Kartal, Calendar Variation ARIMAX, Currency, Inflow, Outflow, Time Series Regression. |
| Subjects: | H Social Sciences > HA Statistics > HA30.3 Time-series analysis |
| Divisions: | Faculty of Mathematics and Science > Statistics |
| Depositing User: | ansi aflacha |
| Date Deposited: | 15 Nov 2019 06:52 |
| Last Modified: | 15 Nov 2019 06:52 |
| URI: | http://repository.its.ac.id/id/eprint/71822 |
Actions (login required)
 |
View Item |