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The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression       1 2 1 2 3 0,106 0, 204 0, 401 329 115 35,9 t t t Z Z Z X t X t X t         and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

Abstract. The purpose of this study is to apply the α-Sutte Indicator and ARIMA in forecasting data. α-Sutte Indicator is a new forecasting method that was developed in 2017 by Ansari Saleh Ahmar. To see the accuracy of these methods, the forecasting results of the α-Sutte Indicator will be forecasting methods compared to other items, namely: ARIMA. Based on the results of forecasting, it is found that α-Sutte Indicator has MSE and MAE values that are lower than other methods (ARIMA). This is supported by MSE data from α-Sutte Indicator smaller than ARIMA(1,1,1).

Previous studies showed that a number of factors play roles in influencing Bitcoin penetration and acceptance, both at country and individual level, such as trust, perceived risk, security threat, perceived benefit, perceived ease of use, as well as macrotechnological and socioeconomic factors. This present study aimed at finding theoretical models at the macro-and microlevels that are able to explain the penetration and acceptance. Study 1 examined hypotheses on the predictive relationship between national cultural orientation and Bitcoin penetration involving 60 countries. Study 2, using a construal level perspective, tested the predictive strength of psychological distances against Bitcoin acceptance, involving 565 Indonesians (M age = 28.88 years, SD age = 12.482 years). The results showed that national culture of individualism, uncertainty avoidance, and long-term orientation are able to predict the penetration. Spatial/physical distance, social distance, and hypothetical distance are able to predict the acceptance. This research is pivotal in obtaining the fundamental factors of community vulnerability in accepting and endorsing new e-money, i.e. Bitcoin. Monetary policy is expected to consider cultural and psychological factors in intervening against economic-technological disruptive innovations developing among societies.