Prasetyo, Jefri Hendra (2017) Implementasi Gabungan Metode Multi-Factors High Order Fuzzy Time Series dengan Fuzzy C-Means untuk Peramalan Tingkat Inflasi di Indonesia. Sarjana thesis, Universitas Brawijaya.
Abstract
Inflasi merupakan fenomena moneter dalam suatu negara dimana naik turunnya mengakibatkan gejolak ekonomi. Bank Central Indonesia menetapkan sasaran inflasi kedepan untuk periode waktu tertentu dengan Inflation Targeting Framework (ITF) sebagai acuan pelaksanaan kebijakan moneter. Jika sasaran inflasi tidak tercapai, maka diperlukan langkah-langkah untuk mengembalikan inflasi sesuai dengan sasaran. Berdasarkan permasalahan tingkat inflasi maka pada penelitian ini diharapkan dapat memberikan sasaran inflasi untuk waktu kedepan melalui peramalan tingkat inflasi menggunakan gabungan metode Multi-Factors High Order Fuzzy Time Series dengan Fuzzy C-Means. Fuzzy C-Means digunakan untuk membentuk subinterval berdasarkan pusat cluster yang diperoleh, penggunaan Fuzzy C-Means diharapkan dapat merefleksikan data asli sehingga menghasilkan peramalan yang lebih baik. Dalam melakukan peramalan digunakan 4-factor data yang meliputi data time series tingkat inflasi beserta 3 faktor yang mempengaruhi. Hasil Implementasi gabungan metode Multi-Factors High Order Fuzzy Time Series dengan Fuzzy C-Means dilakukan pengujian kesalahan dari peramalan menggunakan metode Mean Absolute Percentage Error (MAPE) dan diperoleh nilai kesalahan sebesar sebesar 11.33676% yang menunjukkan bahwa gabungan metode Multi-Factors High Order Fuzzy Time Series dengan Fuzzy C-Means termasuk dalam kateegori baik digunakan dalam peramalan tingkat inflasi di Indonesia karena memiliki nilai akurasi dibawah 20%.
English Abstract
Inflation is a monetary phenomenon in a country where ups and downs result in economic turmoil. Bank Central Indonesia sets the inflation target for the next time with the Inflation Targeting Framework (ITF) as a reference for monetary policy. If the actual inflation does not match the inflation target, then the policy is needed to return inflation to such an inflation target. Based on the inflation rate problem, this research is expected to provide inflation target for the future through inflation rate forecasting using combined Multi-Factors High Order Fuzzy Time Series method with Fuzzy C-Means. Fuzzy C-Means is used to determine the cluster center to be used as a basis for the development of intervals, the use of Fuzzy C-Means is expected to reflect the real data so that the results of forecasting is better. In forecasting used 4-factor data that includes time series data rate inflation and 3 factors that affect. The results of the combined implementation of Multi-Factors High Order Fuzzy Time Series method with Fuzzy C-Means tested the error of forecasting using Mean Absolute Percentage Error (MAPE). Based on the test the error value is 11.33676%, which indicates that the combined method of Multi-Factor High Order Fuzzy Time Series with Fuzzy C-Means is included in the good category used in forecasting the inflation rate in Indonesia because it has an accuracy value below 20%.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2017/527/051707849 |
| Uncontrolled Keywords: | Inflasi, Fuzzy Time Series, Fuzzy C-Means, Multi-Factors High Order Fuzzy Time Series, Mean Absolute Percentage Error (MAPE) |
| Subjects: | 000 Computer science, information and general works > 003 Systems > 003.2 Forecasting and forecasts |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Yusuf Dwi N. |
| Date Deposited: | 28 Aug 2017 07:14 |
| Last Modified: | 25 Sep 2020 12:47 |
| URI: | http://repository.ub.ac.id/id/eprint/1776 |
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