Decision making model amount of water production with comparison double exponential smoothing and triple exponential smoothing
The increasing population growth, of course, has a correlation with the increasing consumption of the amount of clean water needed by the community. Water production management companies need to increase the amount of water production in order to avoid the problem of shortages in meeting water needs...
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creator | Khairina, Dyna Marisa Ramlawati Hatta, Heliza Rahmania Ibrahim, Muhammad Rivani Maharani, Septya Satria, Faisal Yudha |
description | The increasing population growth, of course, has a correlation with the increasing consumption of the amount of clean water needed by the community. Water production management companies need to increase the amount of water production in order to avoid the problem of shortages in meeting water needs which have a detrimental impact on consumers. The emergence of the problem factor in meeting the need for clean water makes the need for a solution to make a decision-making model in the production of the amount of clean water in the future so that adjustments can be made to the amount of water production with the demand for water needs. The data used in this study uses actual data within the previous five years, namely from 2015 to 2019 using the Double Exponential Smoothing (DES) and Triple Exponential Smoothing (TES) calculations using nine alpha values. Forecasting accuracy method used the Mean Absolute Percentage Error (MAPE) method to calculate the percentage error for each alpha value. Based on the results of data processing, comparison testing and verification of results, it shows that the DES method is more superior as a recommended method that can be used to perform calculations as decision support by companies in making decisions to predict the amount of clean water in the future. This is concluded based on the smallest MAPE value in the DES method at alpha 0.4 and the verification results from the tracking signal value which shows the value does not exceed the UCL (Upper Control Limits) and LCL (Lower Control Limits) values in the DES method compared to the TES method. |
doi_str_mv | 10.1063/5.0111583 |
format | Conference Proceeding |
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Water production management companies need to increase the amount of water production in order to avoid the problem of shortages in meeting water needs which have a detrimental impact on consumers. The emergence of the problem factor in meeting the need for clean water makes the need for a solution to make a decision-making model in the production of the amount of clean water in the future so that adjustments can be made to the amount of water production with the demand for water needs. The data used in this study uses actual data within the previous five years, namely from 2015 to 2019 using the Double Exponential Smoothing (DES) and Triple Exponential Smoothing (TES) calculations using nine alpha values. Forecasting accuracy method used the Mean Absolute Percentage Error (MAPE) method to calculate the percentage error for each alpha value. Based on the results of data processing, comparison testing and verification of results, it shows that the DES method is more superior as a recommended method that can be used to perform calculations as decision support by companies in making decisions to predict the amount of clean water in the future. This is concluded based on the smallest MAPE value in the DES method at alpha 0.4 and the verification results from the tracking signal value which shows the value does not exceed the UCL (Upper Control Limits) and LCL (Lower Control Limits) values in the DES method compared to the TES method.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0111583</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Data processing ; Decision making ; Moisture content ; Population growth ; Production management ; Smoothing ; Verification</subject><ispartof>AIP Conference Proceedings, 2023, Vol.2482 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). 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Based on the results of data processing, comparison testing and verification of results, it shows that the DES method is more superior as a recommended method that can be used to perform calculations as decision support by companies in making decisions to predict the amount of clean water in the future. 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Water production management companies need to increase the amount of water production in order to avoid the problem of shortages in meeting water needs which have a detrimental impact on consumers. The emergence of the problem factor in meeting the need for clean water makes the need for a solution to make a decision-making model in the production of the amount of clean water in the future so that adjustments can be made to the amount of water production with the demand for water needs. The data used in this study uses actual data within the previous five years, namely from 2015 to 2019 using the Double Exponential Smoothing (DES) and Triple Exponential Smoothing (TES) calculations using nine alpha values. Forecasting accuracy method used the Mean Absolute Percentage Error (MAPE) method to calculate the percentage error for each alpha value. Based on the results of data processing, comparison testing and verification of results, it shows that the DES method is more superior as a recommended method that can be used to perform calculations as decision support by companies in making decisions to predict the amount of clean water in the future. This is concluded based on the smallest MAPE value in the DES method at alpha 0.4 and the verification results from the tracking signal value which shows the value does not exceed the UCL (Upper Control Limits) and LCL (Lower Control Limits) values in the DES method compared to the TES method.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0111583</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Data processing Decision making Moisture content Population growth Production management Smoothing Verification |
title | Decision making model amount of water production with comparison double exponential smoothing and triple exponential smoothing |
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