Holt-Winters Parameter Optimization Using Dichotomous Search Method (Case Study: PT Telkom Indonesia's Closing Stock Price for the Period January 2019- December 2023)
DOI:
https://doi.org/10.24252/msa.v14i2.58506Keywords:
Holt-Winters, Optimization, Dichotomous Search, Golden Section, MAPEAbstract
Numerical optimization is the process of finding the optimal parameter values in mathematical problems to minimize the objective function. The selection of optimal parameters is the main key in producing prediction accuracy that is close to the actual value in time series forecasting. Determining the optimal parameters in this method is one of the important challenges that must be solved through the numerical optimization approach. Therefore, the application of numerical optimization algorithms such as the Dichotomous Search method is carried out. The optimal parameters obtained are used in the Holt-Winters model to calculate the level, trend, and seasonal components so as to improve the accuracy of time series forecasting. After constructing the Dichotomous Search method algorithm, the optimal parameters will be determined in the Holt-Winters model, and determine the forecasting results using the optimal parameters on the closing stock price data of PT Telkom Indonesia for the period January 2019-December 2023. The application of the Dichotomous Search method is carried out to find the optimal parameter value at 8 evaluation points iteratively. Based on the analysis results, the Dichotomous Search method produces 12 iterations with a MAPE of 6.48449%, so it has high forecasting accuracy.
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https://finance.yahoo.com/quote/TLKM.JK/history?p=TLKM.JK, edisi online, diakses tanggal Januari 2025.
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