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All Journal IJIIS: International Journal of Informatics and Information Systems International Journal for Applied Information Management
Taqwa Hariguna
Department of Information System, Universitas AMIKOM Purwokerto, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences

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Comparison of Three Time Series Forecasting Methods on Linear Regression, Exponential Smoothing and Weighted Moving Average Ajiono Ajiono; Taqwa Hariguna
International Journal of Informatics and Information Systems Vol 6, No 2: March 2023
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v6i2.165

Abstract

The purpose of this study is to compare the 3 forecasting methods Linear Regression, Exponential Smoothing and Weighted Moving Average based on the smallest error value or close to zero. From the results of this study, the Linear Regression method was obtained as the correct method with a predicted value of 502 students, the smallest error value was MAD 27.83, MSE 1152.1 MAPE 8.1%. The Tracking Signal value moves between 1 and -1, the movement is within the control limits of the tracking signal standard deviation distribution 4 and -4, meaning that the method is correct. The Moving Range value moves between 68 and -46, this value is within the MR control limits of 117.83 and -117.83, this result shows that this means that this method has been tested for truth and can be accepted as well. Thus, indicating that the Linear Regression method as a forecasting method is appropriate and acceptable as a basis for future decision making. The level of accuracy of the error and the value in control shows that there is a time series data relationship between the x variable, namely time, and the variable y, namely actual data. In addition, it produces trending data movement patterns, meaning that data movements experience a significant increase over a long period of time or for 7 periods.
An Empirical Study to Understanding Students Continuance Intention Use of Multimedia Online Learning Taqwa Hariguna
International Journal for Applied Information Management Vol. 1 No. 2 (2021): Regular Issue: July 2021
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijaim.v1i2.10

Abstract

The purpose of this study was to assess students' ongoing intentions towards online multimedia learning such as perceived usefulness, ease of use, and flow experience. The sample of this study was 523 students who used off-campus/online learning resources and examined the content of online learning resources and their multimedia aspects. The Extended of Technology Acceptance Model (TAM) was used to predict students' continuing intentions. The results showed that students' intentions were positively influenced by their perceived usefulness, ease of use, and flow experience. It is suggested that the designer of multimedia online learning should be more specific in determining the target users to receive and cultivate a more positive sustainable intention.
Co-Authors Ajiono Ajiono