Modeling and forecasting  metrological factors using  BATS and TBATS models for Keonjhar district of Orissa

Ray, Monika; Sahoo, Kishore Chandra; Abotaleb, Mostafa; Ray, Sourya; Sahu, P.K.; Mishra, Pradeep; Khatib, Abdullah Mohammad Ghazi Al; SankarDas, Soumitra; Jain, Vikas; Balloo, Ritisha

doi:10.54302/mausam.v73i3.1480

Cited by 4 publications

(1 citation statement)

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“…Where: and models the seasonal pattern in time series data using a combination of sine (sin) and cosine (cos) functions (Ray et al, 2022).…”

Section: Tbats Modelmentioning

confidence: 99%

Forecasting Indihome Users By Using Trigonometrics, Box Cox, Transformation, Arma Error, Trend, And Seasonal (TBATS) Methods

Hutagalung,

Sari

2024

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The rapid growth in the use of telecommunication services, particularly IndiHome, has created a pressing need to comprehend and forecast the dynamics of user growth. The swift development of IndiHome services in Pematangsiantar underscores the importance of efficiently forecasting and managing user growth. This research aims to predict future IndiHome users using the TBATS method (Trigonometrics, Box Cox Transformation, Arma Error, Trend, and Seasonal). User data for IndiHome services were obtained from Telekomunikasi Indonesia (Telkom) Pematangsiantar. The collected data underwent analysis and interpolation using the TBATS method. The choice of the TBATS method is attributed to its capability to handle complex patterns of seasonality, trends, and variability in telecommunication service usage data. The TBATS method involves model optimization and model validation using the Mean Absolute Percentage Error (MAPE). The forecasted results for IndiHome users in the next 5 years, with the highest IndiHome users reaching 426,9432, indicate a reasonable forecasting performance. The accuracy of the forecast, as measured by the MAPE calculation, ranges around 30.5%, signifying that the TBATS method demonstrates a satisfactory forecasting capability for IndiHome user data.

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“…Where: and models the seasonal pattern in time series data using a combination of sine (sin) and cosine (cos) functions (Ray et al, 2022).…”

Section: Tbats Modelmentioning

confidence: 99%

Forecasting Indihome Users By Using Trigonometrics, Box Cox, Transformation, Arma Error, Trend, And Seasonal (TBATS) Methods

Hutagalung,

Sari

2024

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Modeling of rainfall time series using NAR and ARIMA model over western Himalaya, India

Rawat

Mishra²,

Ray

et al. 2022

Arab J Geosci

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Modeling and forecasting rainfall patterns in India: a time series analysis with XGBoost algorithm

Mishra,

Al Khatib,

Yadav

et al. 2024

Environ Earth Sci

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Modeling and forecasting metrological factors using BATS and TBATS models for Keonjhar district of Orissa

Cited by 4 publications

References 0 publications

Forecasting Indihome Users By Using Trigonometrics, Box Cox, Transformation, Arma Error, Trend, And Seasonal (TBATS) Methods

Forecasting Indihome Users By Using Trigonometrics, Box Cox, Transformation, Arma Error, Trend, And Seasonal (TBATS) Methods

Modeling of rainfall time series using NAR and ARIMA model over western Himalaya, India

Modeling and forecasting rainfall patterns in India: a time series analysis with XGBoost algorithm

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