Model Hybrid SARIMA (Seasonal Autoregressive Integrated Moving Average ) - ANFIS (Adaptive Neuro Fuzzy Inference System) Pada Data Inflasi Indonesia Tahun 2003-2018

Nida Fauziyah, Anneke Iswani Achmad

Abstract


Abstract. Inflation is is a sustained increase in the general price level of goods and services in an economy over a period of time. Inflation data measured by the inflation rate. Inflation rate needs to be stable, one way to monitor inflation is did  forecasting. Basically, forecasting using the SARIMA Box-Jenkins model has given quite good results but still produces a large error value. To improve the accuracy of forecasting models, a hybrid method is carried out by combining two methods with the condition that both methods consist of linear and nonlinear components. In case of inflation data analysis, the SARIMA Box-Jenkins method is hybridized by the ANFIS method. Based on the analysis of Indonesian inflation data from 2003-2018, the SARIMA model (2,1,0) (0,0,1)12 produces 8,622045% MAPE value . Because the residual of the model is nonlinear, a SARIMA-ANFIS hybrid is carried out so that from the model obtained a MAPE value of 6.270892%. Thus, it is known that the SARIMA-ANFIS hybrid model is a better model than the SARIMA (2,1,0) (0,0,1)12 model for forecasting inflation data because it produces a smaller MAPE value.

Keywords: SARIMA, Box-Jenkis, ANFIS, Hybrid SARIMA-ANFIS, Inflation, MAPE.

Abstrak. Inflasi merupakan kenaikan harga secara umum dan terus menerus dalam suatu waktu. Data inflasi disajikan dalam bentuk laju inflasi. Laju inflasi perlu dipantau agar selalu stabil, sehingga untuk memantau laju inflasi salah satu cara yang dapat dilakukan adalah dengan melakukan peramalan. Pada dasarnya, model peramalan SARIMA Box-Jenkins telah memberikan hasil yang cukup baik namun masih menghasilkan nilai eror yang cukup besar. Dalam upaya untuk meningkatkan akurasi model peramalan, dilakukan suatu metode hybrid yaitu dengan menggabungkan dua metode dengan syarat bahwa kedua metode terdiri dari komponen linear dan nonlinear. Pada kasus analisis data inflasi, metode SARIMA Box-Jenkins di hybrid dengan metode ANFIS. Berdasarkan hasil analisis pada data inflasi indonesia tahun 2003-2018, model SARIMA (2,1,0)(0,0,1)12 menghasilkan nilai MAPE sebesar 8,622045%. Karena residu model tersebut nonlinear, maka dilakukan hybrid SARIMA-ANFIS sehingga dari model tersebut didapatkan nilai MAPE sebesar 6,270892%. Dengan demikian, diketahui bahwa model hybrid SARIMA-ANFIS merupakan model yang lebih baik daripada model SARIMA(2,1,0)(0,0,1)12 untuk peramalan data inflasi karena menghasilkan nilai MAPE lebih kecil.

Kata Kunci: SARIMA, Box-Jenkis, ANFIS, Hybrid SARIMA-ANFIS, Inflasi, MAPE.


Keywords


SARIMA, Box-Jenkis, ANFIS, Hybrid SARIMA-ANFIS, Inflasi, MAPE

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