Ulwiyah, Zuhrofatul (2018) Peramalan Inflow dan Outflow Uang Kartal di Indonesia Menggunakan Model Hibrida Singular Spectrum Analysis dan Adaptive Neuro Fuzzy Inference System. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Indikator jumlah uang beredar dapat dilihat melalui inflow dan outflow. Peramalan inflow dan outflow perlu dilakukan agar terjadi keseimbangan antara jumlah uang beredar dengan kebutuhan masyarakat. Peramalan yang tepat dijadikan informasi yang dapat dipertimbangkan oleh Bank Indonesia untuk perencanaan pengeluaran uang jangka pendek. Pada penelitian ini digunakan model hibrida singular spectrum analysis (SSA) dan adaptive neuro fuzzy inference system (ANFIS) untuk meramalkan inflow dan outflow uang kartal di Indonesia. Terdapat dua kajian yang digunakan yaitu kajian simulasi dan kajian terapan. Penelitian ini menggunakan data inflow dan outflow bulanan di Indonesia mulai bulan Januari 2003 sampai bulan Desember 2016. Hasil dari kajian simulasi menyatakan bahwa pola variasi kalender didekomposisi SSA dalam bentuk musiman atau noise serta peramalan agregat memberikan hasil yang lebih baik daripada peramalan individu. Peramalan SSA-ANFIS pada data pecahan inflow Rp 100.000,00, Rp 20.000,00, Rp 10.000,00, Rp 2.000,00, Rp 1.000,00 dan pecahan outflow Rp 1.000,00 menunjukkan peforma yang lebih baik jika dibandingkan dengan metode ARIMAX.
=============== The indicator of money circulation can be seen through the inflow and outflow. Forecasting inflow and outflow is needed in order to balance the amount of money circulation with the public’s necessary. An appropriate forecasting can serve as information which considered by Bank Indonesia for short-term money spending planning. This research use singular spectrum analysis (SSA) and adaptive neuro fuzzy inference system (ANFIS) model to predict the inflow and outflow of currency in Indonesia. There are two studies that are used,i.e simulation study and case study. This research uses inflow and outflow monthly data of Indonesia start from January 2003 until December 2016. The results from the simulation study showed that the calendar variations pattern decompose by SSA in seasonal or noise pattern. Then, SSA-ANFIS aggregate forecasting show better results than individual forecasting. SSA-ANFIS forecasting on inflow data of Rp 100,000.00, Rp. 20,000.00, Rp 10,000.00, Rp 2,000.00, Rp. 1,000.00 and outflow data of Rp 1,000.00, shows better performance than ARIMAX method.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSMa 519.535 Ulw p |
| Uncontrolled Keywords: | ANFIS; ARIMAX; Inflow; Outflow; SSA |
| Subjects: | H Social Sciences > H Social Sciences (General) > H61.4 Forecasting in the social sciences Q Science > QA Mathematics > QA275 Theory of errors. Least squares. Including statistical inference. Error analysis (Mathematics) |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Zuhrofatul Ulwiyah |
| Date Deposited: | 27 Apr 2018 06:45 |
| Last Modified: | 10 Jul 2020 04:55 |
| URI: | http://repository.its.ac.id/id/eprint/51070 |
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