This study aims to apply time series graphs on stock of Astra Agro Lestari Tbk. and Anadolu Group with last observation carried forward (LOCF) imputation. The imputation was used because the data for the two companies had missing values on several dates. Missing value contained in the company Astra Agro Lestari Tbk. in Indonesia more than Anadolu Group in Turkey because of the difference in the number of holidays. Original data and data with complete dates are combined to form new data where missing values are seen on certain dates. The function used in the R program to form the graph is xts. However, the Date variable has a character class so it needs to be changed to the Date class. The xts function will error if the class is not changed. The modification also causes the horizontal axis of the graph to be replaced by the date. Based on the chart of stock prices and transaction volume of stock of the company Astra Agro Lestari Tbk. and Anadolu Group experienced increases, decreases, and is constant on several dates. Keywords: missing value, R programming, stock prices, transaction volume. MSC2020: 62M10, 91B84, 62-04
This research aimed to form a high-order spatial weighting matrix based on various simulations. The simulation was the determination of the center of the country based on the capital and google trend data. The keywords that have been used in the Google Trends data are "gold price" and "deposit". These keywords have been translated into 6 official languages of the United Nation including Arabic, Chinese, English, French, Russian, and Spanish. Each language has been represented by 1 country. The determination of the country center that has been used based on the capital as well as keywords and time influenced the form of the high-order spatial weighting matrix. In simulations 1, 2, 4, and 5 the highest spatial order formed was 6. It was different with simulations 3, 6, and 7 the highest spatial order formed was 5. Keywords: language, simulation, gold price, deposit.
There have been missing values in the gold price data for Indonesia, Saudi Arabia, and Turkey at the weekend so that imputation techniques have been carried out to solve this problem. The imputation method of replacing NAs with the latest non-NA values also known as last observation carried forward (LOCF) made it a solution to overcome the missing values. This study selected the best -exponential moving average based on the smallest mean absolute percentage error (MAPE) from simulations. The 2-exponential moving average analysis was the best analysis for the price of gold which has missing values in Indonesia, Saudi Arabia, and Turkey during COVID-19, while the largest MAPE values are different for each country.
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