COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY
The number of rainy days is a calculation of the rainy days that occur in one month. In recent years, there has been a decrease in rainy days in some parts of Indonesia. One of the areas at risk of quite a high decreasing number of rainy days is the Bengkulu City area. The decrease in the number of...
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Universitas Pattimura
2022-03-01
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4067 |
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| author | Novi Puspita Farit Mochamad Afendi Bagus Sartono |
| author_facet | Novi Puspita Farit Mochamad Afendi Bagus Sartono |
| author_sort | Novi Puspita |
| collection | DOAJ |
| description | The number of rainy days is a calculation of the rainy days that occur in one month. In recent years, there has been a decrease in rainy days in some parts of Indonesia. One of the areas at risk of quite a high decreasing number of rainy days is the Bengkulu City area. The decrease in the number of rainy days is one of the impacts caused by climate change. The community will feel the impact of climate change-related to the season, especially those working in the agricultural sector. In compiling the planting calendar, it is necessary to consider the seasons to estimate water availability. This study aimed to forecast the data on the number of rainy days in Bengkulu City in the period January 2000 to December 2020 using the Seasonal Autoregressive Integrated Moving Average (SARIMA), Support Vector Regression (SVR), and Genetic Algorithm Support Vector Regression (GA-SVR) methods. The criteria for selecting the best model used was Mean Absolute Deviation (MAD). The MAD value in the SARIMA method was 4,16, 5,07 in the SVR model, and 3,67 in the GA-SVR model. Based on these results, it can be concluded that the GA-SVR model is the best model for forecasting the number of rainy days in Bengkulu City. |
| format | Article |
| id | doaj-art-71069865e7194151a0284ea265553928 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-71069865e7194151a0284ea2655539282025-08-20T04:01:48ZengUniversitas PattimuraBarekeng1978-72272615-30172022-03-0116135536210.30598/barekengvol16iss1pp353-3604067COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITYNovi Puspita0Farit Mochamad Afendi1Bagus Sartono2Statistics and Data Science Study Program, FMIPA, IPB UniversityStatistics and Data Science Study Program, FMIPA, IPB UniversityStatistics and Data Science Study Program, FMIPA, IPB UniversityThe number of rainy days is a calculation of the rainy days that occur in one month. In recent years, there has been a decrease in rainy days in some parts of Indonesia. One of the areas at risk of quite a high decreasing number of rainy days is the Bengkulu City area. The decrease in the number of rainy days is one of the impacts caused by climate change. The community will feel the impact of climate change-related to the season, especially those working in the agricultural sector. In compiling the planting calendar, it is necessary to consider the seasons to estimate water availability. This study aimed to forecast the data on the number of rainy days in Bengkulu City in the period January 2000 to December 2020 using the Seasonal Autoregressive Integrated Moving Average (SARIMA), Support Vector Regression (SVR), and Genetic Algorithm Support Vector Regression (GA-SVR) methods. The criteria for selecting the best model used was Mean Absolute Deviation (MAD). The MAD value in the SARIMA method was 4,16, 5,07 in the SVR model, and 3,67 in the GA-SVR model. Based on these results, it can be concluded that the GA-SVR model is the best model for forecasting the number of rainy days in Bengkulu City.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4067number of rainy dayssarimasvrga-svr |
| spellingShingle | Novi Puspita Farit Mochamad Afendi Bagus Sartono COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY Barekeng number of rainy days sarima svr ga-svr |
| title | COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY |
| title_full | COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY |
| title_fullStr | COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY |
| title_full_unstemmed | COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY |
| title_short | COMPARISON OF SARIMA, SVR, AND GA-SVR METHODS FOR FORECASTING THE NUMBER OF RAINY DAYS IN BENGKULU CITY |
| title_sort | comparison of sarima svr and ga svr methods for forecasting the number of rainy days in bengkulu city |
| topic | number of rainy days sarima svr ga-svr |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4067 |
| work_keys_str_mv | AT novipuspita comparisonofsarimasvrandgasvrmethodsforforecastingthenumberofrainydaysinbengkulucity AT faritmochamadafendi comparisonofsarimasvrandgasvrmethodsforforecastingthenumberofrainydaysinbengkulucity AT bagussartono comparisonofsarimasvrandgasvrmethodsforforecastingthenumberofrainydaysinbengkulucity |