Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters
Unhealthy and unsafe sanitation will make it easier for various diseases to attack the body. In addition, unsafe sanitation will also affect a country's economy, including declining welfare, tourism losses, and environmental losses due to the loss of productive land. The research aimed to estim...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Politeknik Negeri Padang
2023-02-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | https://joiv.org/index.php/joiv/article/view/1685 |
| _version_ | 1811159854521253888 |
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| author | Suwardi Annas Ansari Saleh Ahmar Rahmat Hidayat |
| author_facet | Suwardi Annas Ansari Saleh Ahmar Rahmat Hidayat |
| author_sort | Suwardi Annas |
| collection | DOAJ |
| description | Unhealthy and unsafe sanitation will make it easier for various diseases to attack the body. In addition, unsafe sanitation will also affect a country's economy, including declining welfare, tourism losses, and environmental losses due to the loss of productive land. The research aimed to estimate the welfare cost of premature deaths based on unsafe sanitation risks using the SutteARIMA, Neural Network Time Series, and Holt-Winters. The study analyzed estimates and projections of the welfare cost of premature deaths based on the risks of unsafe sanitation of BRICS countries (Brazil, Russia, Indonesia, China, and South Africa). The data in this research used secondary data. Secondary time series data was taken from the Environment Database of the OECD. Stat. (Mortality and welfare cost from exposure to environmental risks). The data on the study was based on variables: welfare cost of premature deaths, % GDP equivalent, risk: unsafe sanitation, age: all, sex: both, unit: percentage, and data from 2005 to 2019. The three forecasting methods (SutteARIMA, Neural Network Time Series, and Holt-Winters) were juxtaposed in fitting data to see the forecasting methods' reliability and accuracy. The accuracy of forecasting results was compared based on MAPE and MSE values. The results of the research showed that the SutteARIMA and NNAR(1,1) methods were best used to predict the welfare cost of premature deaths in view of unsafe sanitation risks for BRICS countries. |
| first_indexed | 2024-04-10T05:47:55Z |
| format | Article |
| id | doaj.art-c326294b3da94c648be2595a2b0b9030 |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-04-10T05:47:55Z |
| publishDate | 2023-02-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-c326294b3da94c648be2595a2b0b90302023-03-05T10:27:22ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042023-02-017115316010.30630/joiv.7.1.1685481Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-WintersSuwardi Annas0Ansari Saleh Ahmar1Rahmat Hidayat2Universitas Negeri Makassar, Makassar, 90223, IndonesiaUniversitas Negeri Makassar, Makassar, 90223, IndonesiaPoliteknik Negeri Padang, Padang, 25164, IndonesiaUnhealthy and unsafe sanitation will make it easier for various diseases to attack the body. In addition, unsafe sanitation will also affect a country's economy, including declining welfare, tourism losses, and environmental losses due to the loss of productive land. The research aimed to estimate the welfare cost of premature deaths based on unsafe sanitation risks using the SutteARIMA, Neural Network Time Series, and Holt-Winters. The study analyzed estimates and projections of the welfare cost of premature deaths based on the risks of unsafe sanitation of BRICS countries (Brazil, Russia, Indonesia, China, and South Africa). The data in this research used secondary data. Secondary time series data was taken from the Environment Database of the OECD. Stat. (Mortality and welfare cost from exposure to environmental risks). The data on the study was based on variables: welfare cost of premature deaths, % GDP equivalent, risk: unsafe sanitation, age: all, sex: both, unit: percentage, and data from 2005 to 2019. The three forecasting methods (SutteARIMA, Neural Network Time Series, and Holt-Winters) were juxtaposed in fitting data to see the forecasting methods' reliability and accuracy. The accuracy of forecasting results was compared based on MAPE and MSE values. The results of the research showed that the SutteARIMA and NNAR(1,1) methods were best used to predict the welfare cost of premature deaths in view of unsafe sanitation risks for BRICS countries.https://joiv.org/index.php/joiv/article/view/1685forecastingwelfare costpremature deathsunsafe sanitationsuttearimannarholt-winters. |
| spellingShingle | Suwardi Annas Ansari Saleh Ahmar Rahmat Hidayat Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters JOIV: International Journal on Informatics Visualization forecasting welfare cost premature deaths unsafe sanitation suttearima nnar holt-winters. |
| title | Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters |
| title_full | Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters |
| title_fullStr | Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters |
| title_full_unstemmed | Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters |
| title_short | Predicting the Welfare Cost of Premature Deaths Based on Unsafe Sanitation Risk using SutteARIMA and Comparison with Neural Network Time Series and Holt-Winters |
| title_sort | predicting the welfare cost of premature deaths based on unsafe sanitation risk using suttearima and comparison with neural network time series and holt winters |
| topic | forecasting welfare cost premature deaths unsafe sanitation suttearima nnar holt-winters. |
| url | https://joiv.org/index.php/joiv/article/view/1685 |
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