VANNESHA, VANNESHA and Rini, Dian Palupi (2025) PENERAPAN METODE FUZZY TIME SERIES LEE YANG DIOPTIMASI DENGAN PARTICLE SWARM OPTIMIZATION UNTUK PREDIKSI NILAI TUKAR RUPIAH. Undergraduate thesis, Sriwijaya University.
![[thumbnail of RAMA_55201_09021382126144_cover.jpg]](http://repository.unsri.ac.id/182382/1/RAMA_55201_09021382126144_cover.jpg)  Preview |
Image
RAMA_55201_09021382126144_cover.jpg - Cover Image Available under License Creative Commons Public Domain Dedication. Download (63kB) | Preview |
![[thumbnail of RAMA_55201_09021382126144.pdf]](http://repository.unsri.ac.id/style/images/fileicons/text.png) |
Text
RAMA_55201_09021382126144.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) |
|
Text
RAMA_55201_09021382126144_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (6MB) |
|
Text
RAMA_55201_09021382126144_0023027804_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (5MB) |
|
Text
RAMA_55201_09021382126144_0023027804_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) |
|
Text
RAMA_55201_09021382126144_0023027804_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) |
|
Text
RAMA_55201_09021382126144_0023027804_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (9MB) |
|
Text
RAMA_55201_09021382126144_0023027804_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (6MB) |
|
Text
RAMA_55201_09021382126144_0023027804_06.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (617kB) |
|
Text
RAMA_55201_09021382126144_0023027804_07_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (336kB) |
|
Text
RAMA_55201_09021382126144_0023027804_08_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (3MB) |
Abstract
Currency exchange rate fluctuations have a significant impact on a country's economic stability, affecting prices, interest rates, production, and competitiveness. Factors such as global inflation, interest rates, and international political conditions further increase uncertainty. Therefore, an accurate exchange rate prediction system is needed to aid decision-making. One method that can be used is the Fuzzy Time Series Lee (FTS Lee) model, which has the ability to handle linguistic data and uncertainty, but still has limitations in parameter selection. To address this, the Particle Swarm Optimization (PSO) algorithm is used to optimize the FTS Lee parameters to better align with the data characteristics. This study predicts the exchange rate of the Rupiah against three currencies: USD, GBP, and JPY. The results show a significant improvement in accuracy after optimization. For USD, MAPE decreased from 0.3256% to 0.1520%; for GBP from 0.2888% to 0.1390%; and for JPY from 0.3174% to 0.1023%. The optimal configuration differs for each currency, demonstrating the flexibility of PSO in adjusting parameters. The combination of FTS Lee and PSO has proven capable of improving the performance of the prediction model, as well as providing practical contributions in the fields of economics and finance, particularly in anticipating exchange rate fluctuations.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Nilai Tukar, Fuzzy Time Series Lee, Particle Swarm Optimization |
| Subjects: | T Technology > T Technology (General) > T1-995 Technology (General) |
| Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
| Depositing User: | Vannesha Vannesha |
| Date Deposited: | 06 Aug 2025 01:51 |
| Last Modified: | 06 Aug 2025 01:51 |
| URI: | http://repository.unsri.ac.id/id/eprint/182382 |
Actions (login required)
 |
View Item |