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All Journal IJIIS: International Journal of Informatics and Information Systems Journal of Applied Data Sciences
Taqwa Hariguna
Department of Information System, Universitas AMIKOM Purwokerto, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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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.
The Empirical Study of Usability and Credibility on Intention Usage of Government-to-Citizen Services Tsang-Hsiang Cheng; Shih-Chih Chen; Taqwa Hariguna
Journal of Applied Data Sciences Vol 2, No 2: MAY 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i2.30

Abstract

E-government allows governments to service citizens in a more timely, effective, and cost-efficient method. The most popular benefits of Government-to-Citizen (G2C)are the simple posting of forms and registrations, serve citizens, improvement of education information and e-voting. This paper analyzes the influence of website usability and the credibility on both citizen satisfaction and citizen intention to use an e-government website, as well as the impact of citizen satisfaction on citizen intentions. To prove the validity of our proposed research model, empirical analysis was performed with 366 valid questionnaires using Partial Least Square. The results of the research show that credibility of website e-government usage had significant effects on citizen satisfaction which in turn affects citizen intention to use, and citizen satisfaction also significantly affected citizen intention to use. However, the usability of e-government websites slightly influences citizen satisfaction and citizen intention to use.
Co-Authors Ajiono Ajiono Shih-Chih Chen Tsang-Hsiang Cheng