Forecasting Model of Amount of Water Production Using Double Moving Average Method

D. M. Khairina, S. Maharani, P. P. Widagdo, Ramlawati, H. R. Hatta
{"title":"Forecasting Model of Amount of Water Production Using Double Moving Average Method","authors":"D. M. Khairina, S. Maharani, P. P. Widagdo, Ramlawati, H. R. Hatta","doi":"10.1109/IC2IE50715.2020.9274603","DOIUrl":null,"url":null,"abstract":"The population continues to increase causing high water consumption. This causes the need for clean water to continue to increase while the supply of clean water is uncertain every year. Uncontrolled use of water is a challenge for the organization in meeting clean water needs. A forecasting system is needed that is able to predict the use of water for several periods in order to minimize the problem of uneven water distribution. Water demand predictions can also be utilized by companies to allocate water distribution to customers so that they do not experience shortages or waste. Forecasting the amount of water production is carried out using actual data within the period of 2 (two) previous years ie from 2017 to 2018 using the Double Moving Average (DMA) method. Forecasting trials are carried out by comparing the actual data of 2018 with the estimated data of 2018 by using the movement value of 3 periods and 4 periods. The forecasting accuracy method is used the Mean Absolute Percentage Error (MAPE) method to calculate the percentage of errors at each method movement value DMA every month. Based on the tests conducted, the best forecast of the amount of water production is shown in the movement value with 3 periods which results in a smaller accuracy or error rate of MAPE so that it can be said the accuracy value is better and more recommended than the movement value with 4 periods in the DMA method so determining the value of movement can affect the value of forecasting accuracy.","PeriodicalId":211983,"journal":{"name":"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC2IE50715.2020.9274603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

The population continues to increase causing high water consumption. This causes the need for clean water to continue to increase while the supply of clean water is uncertain every year. Uncontrolled use of water is a challenge for the organization in meeting clean water needs. A forecasting system is needed that is able to predict the use of water for several periods in order to minimize the problem of uneven water distribution. Water demand predictions can also be utilized by companies to allocate water distribution to customers so that they do not experience shortages or waste. Forecasting the amount of water production is carried out using actual data within the period of 2 (two) previous years ie from 2017 to 2018 using the Double Moving Average (DMA) method. Forecasting trials are carried out by comparing the actual data of 2018 with the estimated data of 2018 by using the movement value of 3 periods and 4 periods. The forecasting accuracy method is used the Mean Absolute Percentage Error (MAPE) method to calculate the percentage of errors at each method movement value DMA every month. Based on the tests conducted, the best forecast of the amount of water production is shown in the movement value with 3 periods which results in a smaller accuracy or error rate of MAPE so that it can be said the accuracy value is better and more recommended than the movement value with 4 periods in the DMA method so determining the value of movement can affect the value of forecasting accuracy.
双移动平均法预测出水量模型
人口持续增长导致高用水量。这导致对清洁水的需求继续增加,而清洁水的供应每年都不确定。不受控制的用水是该组织在满足清洁用水需求方面面临的挑战。需要一种能够预测几个时期的用水情况的预报系统,以便尽量减少水分配不均匀的问题。水需求预测也可以被公司用来分配给客户的水,这样他们就不会遇到短缺或浪费。使用双移动平均线(DMA)方法,使用前2(2)年(即2017年至2018年)的实际数据进行产水量预测。采用3期和4期的移动值,将2018年的实际数据与2018年的估计数据进行对比,进行预测试验。预测精度方法采用平均绝对误差百分比法(MAPE)计算每个月各方法移动值DMA的误差百分比。通过试验发现,3周期的运动值对产水量的预测效果最好,MAPE的精度或错误率较小,可以说该精度值比DMA法中4周期的运动值更好,更值得推荐,因此运动值的确定会影响预测精度值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信