How to cite (IEEE): S. Annas, A. Saleh Ahmar, & R. 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, vol. 7, no. 1, , pp. 153-160, Feb. 2023. https://doi.org/10.30630/joiv.7.1.1685

How to cite (APA): Annas, S., Saleh Ahmar, A., & Hidayat, R. (2023). 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, 7(1), 153-160. https://doi.org/10.30630/joiv.7.1.1685

How to cite (Chicago): Annas, Suwardi, Saleh Ahmar, Ansari, AND Hidayat, Rahmat. "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 [Online], Volume 7 Number 1 (27 February 2023) https://doi.org/10.30630/joiv.7.1.1685

How to cite (Vancouver): Annas S, Saleh Ahmar A, & Hidayat R . 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 [Online]. 2023 Feb; 7(1):153-160. https://doi.org/10.30630/joiv.7.1.1685

How to cite (Harvard): Annas, S., Saleh Ahmar, A., & Hidayat, R. ,2023. 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, [Online] 7(1), pp. 153-160. https://doi.org/10.30630/joiv.7.1.1685

How to cite (MLA8): Annas, Suwardi, 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 [Online], 7.1 (2023): 153-160. Web. 1 Jun. 2023 , https://doi.org/10.30630/joiv.7.1.1685

BibTex Citation Data :

@article{JOIV1685,
    	author = {Suwardi Annas and Ansari Saleh Ahmar and Rahmat Hidayat},
    	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},
    	journal = {JOIV : International Journal on Informatics Visualization},
    	volume = {7},
    	number = {1},
    	year = {2023},
    	keywords = {Forecasting; welfare cost; premature deaths; unsafe sanitation; SutteARIMA; NNAR; holt-winters.},
    	abstract = {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.},
        	issn = {2549-9904},    	pages = {153--160},    	doi = {10.30630/joiv.7.1.1685},
        	url = {http://joiv.org/index.php/joiv/article/view/1685}
    }
    

Refworks Citation Data :

@article{{JOIV}{1685}, author = {Annas, S., Saleh Ahmar, A., Hidayat, R.}, 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}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {7}, number = {1}, year = {2023}, doi = {10.30630/joiv.7.1.1685}, url = {} }