Pub Date : 2020-09-15DOI: 10.1109/IC2IE50715.2020.9274603
D. M. Khairina, S. Maharani, P. P. Widagdo, Ramlawati, H. R. Hatta
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.
{"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":"https://doi.org/10.1109/IC2IE50715.2020.9274603","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":0.0,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125938155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-15DOI: 10.1109/IC2IE50715.2020.9274615
Risna Sari, Retno Widianti
Employee scheduling is a complex problem since it must precisely allocate resources such as time, task disposition, employee’s competencies, a day off, and cost of the activity. The firefly algorithm is implemented to arrange the schedule of employees automatically and meet the rules. This algorithm allows the system to produce a list that is by applicable rules. The proposed system was designed with three steps to produce lists of employee shifts. Firstly, enter employee, job description and the last is set the employee holiday schedules. Then the system will process it and produce the desired schedule in a short time. Performance results show schedule made in 90 seconds with a success rate of 96.5% with 20 fireflies and 40 times iteration
{"title":"Optimizing Employee Scheduling System with Firefly Algorithm (Case Study: MJ Store)","authors":"Risna Sari, Retno Widianti","doi":"10.1109/IC2IE50715.2020.9274615","DOIUrl":"https://doi.org/10.1109/IC2IE50715.2020.9274615","url":null,"abstract":"Employee scheduling is a complex problem since it must precisely allocate resources such as time, task disposition, employee’s competencies, a day off, and cost of the activity. The firefly algorithm is implemented to arrange the schedule of employees automatically and meet the rules. This algorithm allows the system to produce a list that is by applicable rules. The proposed system was designed with three steps to produce lists of employee shifts. Firstly, enter employee, job description and the last is set the employee holiday schedules. Then the system will process it and produce the desired schedule in a short time. Performance results show schedule made in 90 seconds with a success rate of 96.5% with 20 fireflies and 40 times iteration","PeriodicalId":211983,"journal":{"name":"2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)","volume":"308 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133196305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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