{"title":"东加里曼丹主要城市通货膨胀预测:基于Holt-Winters和SARIMA模型的比较","authors":"Regi Muzio Ponziani","doi":"10.33005/ijdasea.v1i2.8","DOIUrl":null,"url":null,"abstract":"This research aims to compare the performance of Holt Winters and Seasonal Autoregressive Integrate\n Moving Average (SARIMA) models in predicting inflation in Balikpapan and Samarinda, two biggest cities in\n East Kalimantan province. The importance of East Kalimantan province cannot be overstated since it has been\n declared as the venue for the capital of Indonesia. Hence, inflation prediction of the two cities will give\n valuable insights about the economic nature of the province for the country’s new capital. The data used in\n this study extended from January 2015 to September 2021. The data were divided into training and test data.\n The training data were used to model the time series equation using Holt winters and SARIMA models. Later,\n the models derived from training data were employed to produce forecasts. The forecasts were compared to the\n actual inflation data to determine the appropriate model for forecasting. Test data were from January 2015\n to December 2020 and test data extended from January 2021 to September 2021. The result showed that\n Holt-Winters performed better than SARIMA in prediction inflation. The Root Mean Squared Error (RMSE) values\n are lower for Holt-Winters Exponential Smoothing for both cities. It also predicts better timing of\n cyclicality than SARIMA model.","PeriodicalId":220622,"journal":{"name":"Internasional Journal of Data Science, Engineering, and Anaylitics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Inflation Forecasting of Major Cities In East Kalimantan: A Comparison Of Holt-Winters And SARIMA\\n Model\",\"authors\":\"Regi Muzio Ponziani\",\"doi\":\"10.33005/ijdasea.v1i2.8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research aims to compare the performance of Holt Winters and Seasonal Autoregressive Integrate\\n Moving Average (SARIMA) models in predicting inflation in Balikpapan and Samarinda, two biggest cities in\\n East Kalimantan province. The importance of East Kalimantan province cannot be overstated since it has been\\n declared as the venue for the capital of Indonesia. Hence, inflation prediction of the two cities will give\\n valuable insights about the economic nature of the province for the country’s new capital. The data used in\\n this study extended from January 2015 to September 2021. The data were divided into training and test data.\\n The training data were used to model the time series equation using Holt winters and SARIMA models. Later,\\n the models derived from training data were employed to produce forecasts. The forecasts were compared to the\\n actual inflation data to determine the appropriate model for forecasting. Test data were from January 2015\\n to December 2020 and test data extended from January 2021 to September 2021. The result showed that\\n Holt-Winters performed better than SARIMA in prediction inflation. The Root Mean Squared Error (RMSE) values\\n are lower for Holt-Winters Exponential Smoothing for both cities. It also predicts better timing of\\n cyclicality than SARIMA model.\",\"PeriodicalId\":220622,\"journal\":{\"name\":\"Internasional Journal of Data Science, Engineering, and Anaylitics\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internasional Journal of Data Science, Engineering, and Anaylitics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33005/ijdasea.v1i2.8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internasional Journal of Data Science, Engineering, and Anaylitics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33005/ijdasea.v1i2.8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Inflation Forecasting of Major Cities In East Kalimantan: A Comparison Of Holt-Winters And SARIMA
Model
This research aims to compare the performance of Holt Winters and Seasonal Autoregressive Integrate
Moving Average (SARIMA) models in predicting inflation in Balikpapan and Samarinda, two biggest cities in
East Kalimantan province. The importance of East Kalimantan province cannot be overstated since it has been
declared as the venue for the capital of Indonesia. Hence, inflation prediction of the two cities will give
valuable insights about the economic nature of the province for the country’s new capital. The data used in
this study extended from January 2015 to September 2021. The data were divided into training and test data.
The training data were used to model the time series equation using Holt winters and SARIMA models. Later,
the models derived from training data were employed to produce forecasts. The forecasts were compared to the
actual inflation data to determine the appropriate model for forecasting. Test data were from January 2015
to December 2020 and test data extended from January 2021 to September 2021. The result showed that
Holt-Winters performed better than SARIMA in prediction inflation. The Root Mean Squared Error (RMSE) values
are lower for Holt-Winters Exponential Smoothing for both cities. It also predicts better timing of
cyclicality than SARIMA model.