TSA App by R Shiny : Time Series Analysis Application for Univariate Series Data

Tri Utomo, Agung
Ahmar, Ansari Saleh
Aidid, Muhammad Kasim
Rais, Zulkifli
Alfairus, Muh. Qodri

ARRUS Journal of Engineering and Technology
Vol. 5 No. 1 (2025)

Time series analysis is a statistical method used to model and forecast sequential data over time. This modeling is typically performed using software, but most analytical tools require paid licenses. To address this issue, the TSA App by R Shiny is developed as an open-source application that is easily accessible. The application features a dashboard-based interface designed to help users perform univariate time series analysis without requiring programming skills. This study compares the analysis results of the TSA App with other software such as R Studio, Minitab, and Python. The results show that the TSA App produces comparable outputs in terms of visualization, ARIMA modeling, and forecasting accuracy. Therefore, the TSA App provides a practical and legal solution for time series analysis, especially for users who are unfamiliar with coding.