KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Kuharattanachai, ChoojaiSubject: search.filters.subject.Box-Jenkins method

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    FORECASTING MODELS FOR FIRST YEAR PREMIUM OF LIFE INSURANCE
    (2022-01-01)
    Banditvilai, Somsri
    ;
    Kuharattanachai, Choojai
    The objective of this research is to study forecasting models for the first year premium of life insurance. The premium data are gathered from the Office of Insurance Commission (OIC) during January 2003 to November, 2021. The data are divided into 2 sets. The first set from January, 2003 to December 2020 is used for constructing and selection the forecasting models. The second one from January 2021 to November 2021 is used for computing the accuracy of the forecasting model. The forecasting models are chosen by considering the minimum Root Mean Square Error (RMSE). The Mean Absolute Percentage Error (MAPE) is used to measure the accuracy of the model. The results showed that the multiplicative model with initial values from 18 years Decomposition method give the appropriate model for the first year premium of life insurance and yields the MAPE = 17.29%
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Forecasting the Number of Hat Yai International Airport Passengers
    (2021-06-04)
    Banditvilai, Somsri
    ;
    Kuharattanachai, Choojai
    The objective of this research is to compare three forecasting techniques of the Holt-Winters method with different initial values, the Bagging Holt-Winters method, and Box-Jenkins method based on the number of monthly Hat Yai International airport passengers from January 2003 to December 2019 which have both non-linear trend and seasonal variation. The data are collected by the Airport of Thailand Public Company Limited. The data are divided into 2 sets. The first set from January 2003 to December 2018 is used to construct the models and employed minimum Root Mean Square Error (RMSE) and residuals have normal distribution for model selection. The second set is from January 2019 to December 2019 which is used to compute the accuracy of forecasting models by using the Mean Absolute Percentage Error (MAPE). The results show that the additive Bagging Holt-Winters model gives the minimum RMSE = 9,0031.66 for the first set and yields MAPE = 11.66% for the second one.