Model Fungsi Transfer Input Ganda untuk Pemodelan Jakarta Islamic Index

2019 ◽  
Vol 7 (3) ◽  
Author(s):  
Nur Laela Fitriani ◽  
Pika Silvianti ◽  
Rahma Anisa
Keyword(s):  
Exchange Rate ◽  
Transfer Function ◽  
Multivariate Time Series ◽  
Model Identification ◽  
Transfer Function Model ◽  
Function Model ◽  
Jones Index ◽  
Multiple Input ◽  
Identification Stage ◽  
Stage Estimation

Transfer function model with multiple input is a multivariate time series forecasting model that combines several characteristics of ARIMA models by utilizing some regression analysis properties. This model is used to determine the effect of output series towards input series so that the model can be used to analyze the factors that affect the Jakarta Islamic Index (JII). The USD exchange rate against rupiah and Dow Jones Index (DJI) were used as input series. The transfer function model was constructed through several stages: model identification stage, estimation of transfer function model, and model diagnostic test. Based on the transfer function model, the JII was influenced by JII at the period of one and two days before. JII was also affected by the USD exchange rate against rupiah at the same period and at one and two days before. In addition, the JII was influenced by DJI at the same period and also at period of one until five days ago. The Mean Absolute Prencentage Error (MAPE) value of forecasting result was 0.70% and the correlation between actual and forecast data was 0.77. This shows that the model was well performed for forecasting JII.

scholarly journals PERAMALAN JUMLAH KUNJUNGAN WISATAWAN MANCANEGARA YANG BEKUNJUNG KE BALI MENGGUNAKAN FUNGSI TRANSFER

2016 ◽  
Vol 5 (4) ◽  
pp. 139
Author(s):  
I KETUT PUTRA ADNYANA ◽  
I WAYAN SUMARJAYA ◽  
I KOMANG GDE SUKARSA
Keyword(s):  
Exchange Rate ◽  
Transfer Function ◽  
Multivariate Time Series ◽  
Arima Model ◽  
Information Criterion ◽  
Percentage Error ◽  
Transfer Function Model ◽  
Function Model ◽  
Diagnostic Checking ◽  
The Exchange Rate

The aim of this research is to model and forecast the number of tourist arrivals to Bali using transfer function model based on exchange rate USD to IDR from January 2009 to December 2015. Transfer function model is a multivariate time series model which can be used to identify the effect of the exchange rate to the number of tourist arrivals to Bali. The first stage in transfer function modeling is identification of ARIMA model in exchange rate USD to IDR variable. The best ARIMA model is chosen based on the smallest Akaike information criterion (AIC). The next stage are as follows identification of transfer function model, estimation of transfer function model, and diagnostic checking for transfer function model. The estimated transfer function model suggests that the number of tourist arrivals to Bali is affected by the exchange rate of the previous eight months. The mean absolute percentage error (MAPE) is equal of the forecasting model to 9,62%.

scholarly journals Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City

CAUCHY ◽  
2017 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Priska Arindya Purnama
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Transfer Function ◽  
Air Temperature ◽  
Multivariate Time Series ◽  
Time Series Model ◽  
Transfer Function Model ◽  
Air Humidity ◽  
Rainfall Forecasting ◽  
Function Model

The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Y<sub>t</sub>) sequence expected to be effected by an input series (X<sub>t</sub>) and other inputs in a group called a noise series (N<sub>t</sub>). Multi input transfer function model obtained is (<em>b<sub>1</sub>,s<sub>1</sub>,r<sub>1</sub></em>) (<em>b<sub>2</sub>,s<sub>2</sub>,r<sub>2</sub></em>) (<em>b<sub>3</sub>,s<sub>3</sub>,r<sub>3</sub></em>) (<em>b<sub>4</sub>,s<sub>4</sub>,r<sub>4</sub></em>)(<em>p<sub>n</sub>,q<sub>n</sub></em>) = (0,0,0) (23,0,0) (1,2,0) (0,0,0) ([5,8],2) and shows that air temperature on t-day affects rainfall on t-day, rainfall on t-day is influenced by air humidity in the previous 23 days, rainfall on t-day is affected by wind speed in the previous day , and rainfall on day t is affected by clouds on day t. The results of rainfall forecasting in Batu City with multi input transfer function model can be said to be accurate, because it produces relatively small RMSE value. The value of RMSE data forecasting training is 7.7921 while forecasting data testing is 4.2184. Multi-input transfer function model is suitable for rainfall in Batu City.

scholarly journals Analisis Pengaruh Kurs USD terhadap Jakarta Islamic Index dengan Menggunakan Model Fungsi Transfer

2018 ◽  
Vol 2 (2) ◽  
pp. 66-72
Author(s):  
Pika Silvianti ◽  
Nur Laela Fitriani
Keyword(s):  
Exchange Rate ◽  
Transfer Function ◽  
Explanatory Variable ◽  
Arima Model ◽  
Diagnostic Testing ◽  
Forecasting Model ◽  
Transfer Function Model ◽  
Function Model ◽  
Model Diagnostic ◽  
The Exchange Rate

The transfer function model is a time series forecasting model that combines several characteristics ofthe ARIMA model one variable with several characteristics of regression analysis. This model is used to determine the effect of an explanatory variable (input series) on the response variable (output series). This study uses a transfer function model to analyze the effect of the exchange rate on Jakarta Islamic Index. The transfer function model is structured through several stages, starting from modelidentification, estimation of the transfer function model, and model diagnostic testing. Based on the transfer function model, Jakarta Islamic Index was influenced by Jakarta Islamic Index in one and two days earlier and the exchange rate in the same period and one to two days earlier. The forecasting MAPE value of 0.6529% shows that the transfer function model obtained is good enough in forecasting.

scholarly journals Exchange Rate and Interest Rate in the Monetary Policy Reaction Function

2017 ◽  
Vol 6 (1) ◽  
pp. 55-86 ◽  
Author(s):  
Borivoje D. Krušković
Keyword(s):  
Exchange Rate ◽  
Data Analysis ◽  
Interest Rate ◽  
Transfer Function ◽  
Regression Model ◽  
Multiple Regression ◽  
Multiple Regression Model ◽  
Emerging Countries ◽  
Transfer Function Model ◽  
Function Model

Abstract In recent years there has been a particular interest in the relation between exchange rates and interest rates both in developed countries and emerging countries. This is understandable given the important role that these variables have in determining the movement of nominal and real economic variables, including the movement of domestic inflation, real output, exports and imports, foreign exchange reserves, etc. To realized the importance of the given instruments selected macroeconomic indicators, data analysis (monthly data) relating to Serbia was made on the basis of the Transfer Function Model, a data analysis (annual data) relating to emerging countries was done on the basis of the Stepvise Multiple Regression model. In the transfer function model we used the Maximum Likelihood method for assessing unknown coefficients. In the gradual multiple regression model we used the Least Square method for the evaluation of unknown coefficients. All indicator values were used in the original unmodified form, i.e. there was no need for a variety of transformations. Empirical analysis showed that the exchange rate is a more significant transmission mechanism than the interest rate both in emerging markets and Serbia.

scholarly journals Administrative Costs and Tariff Rates in the Presence of Customs Evasion: Evidence from Ecuador

Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 21
Author(s):  
Jazmín González Aguirre ◽  
Alberto Del Villar
Keyword(s):  
International Trade ◽  
Transfer Function ◽  
Gross Domestic Product ◽  
Foreign Trade ◽  
Transfer Function Model ◽  
Administrative Cost ◽  
Function Model ◽  
Administrative Costs ◽  
Tariff Rates ◽  
Budgetary Expenditure

This paper seeks to assess the effectiveness of customs policies in increasing the resources devoted to controlling and inspection. Specifically, it seeks to analyze whether an increase in the administrative cost of collecting taxes on foreign trade in Ecuador contributes to reducing customs fraud. To this end, we identify and estimate a transfer function model (ARIMAX), considering information on foreign trade such as official international trade statistics report and tariff rates, as well as the execution of budgetary expenditure and Ecuador’s gross domestic product (GDP). The period under study includes quarterly series from 2006 to 2018. The results obtained by the model indicate that allocating greater material and budgetary resources to combat customs fraud does not always achieve the objective of reducing customs evasion.

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