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Journal : International Journal of Industrial Engineering and Engineering Management

The Effect of Increasing Daily Case COVID-19 as Moderating Variable on Coal Stock Price Ratna Mustika Dewi; Anne Mudya Yolanda
International Journal of Industrial Engineering and Engineering Management Vol. 3 No. 2 (2021)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v3i2.5547

Abstract

Stock investments in the time of the COVID-19 pandemic have a considerable risk. This happens because of the increasingly uncontrolled movement of stock prices. The potential for steep charts can occur at any time. Sentiment analysis of increasing daily cases of COVID-19 was analyzed to see how much effect it has on stock price movements. This research will analyze stock prices from coal commodities in Indonesia. Researchers choose to discuss coal commodities because, in April 2021, there was a significant increase and highest in November 2021. Because of the data, researchers want to see the influence of some coal companies using selling price data with moderating variables for estimating the stock price. There are 26 coal companies that are listed on Indonesia Stock Exchange. The analysis will be a check on five companies that have the largest investors. The analysis is also carried out on coal sales price movements. Furthermore, five different coal mining companies were analyzed based on the rate of price changes to new selling prices with variable moderation in Indonesia. Increasing daily cases of COVID-19 being variable moderation. The method used for finding the relationship is a linear regression with a moderating variable. According to the analysis, the increasing daily case of COVID-19 as a moderating variable is enough to affect the relationship between the selling price of coal and the stock price of HRUM.JK and PTBA.JK. In stock price HRUM.JK, there is an increasing adjusted R square from 0.5254 to 0.5451. The same conditions apply to PTBA.JK has increased by 0.4040 to 0.4444.
Forecasting Non-Oil and Gas Exports in Indonesia Using Double and Triple Exponential Smoothing Methods Bustami; Anne Mudya Yolanda; Nisha Thahira
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.6211

Abstract

Non-oil and gas exports could be forecasted using exponential smoothing for future periods. This study examines non-oil and gas export data in Indonesia from January 2015 to May 2021, indicating trends and seasonality. Based on the data characteristics, the obtained data were analyzed using Holt's double exponential smoothing method and triple exponential smoothing with multiplicative and additives Holt-Winters. The MAPE for all three models is less than 10%, indicating that the method is very good and could be used to forecast the next period. Using MAPE as a comparison, the best model for non-oil and gas exports is the additive Holt-Winters method triple exponential smoothing, which has the lowest MAPE of any model. The best method was employed to forecast data, making it possible for us to anticipate the pattern of non-oil and gas exports. This forecast data could be used as the basis for policymakers' decision-making. The forecast results using this method indicate that the value of non-oil exports will increase for the next period.