Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm
In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)
2022-09-01
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| Series: | Journal of Applied Engineering and Technological Science |
| Subjects: | |
| Online Access: | https://journal.yrpipku.com/index.php/jaets/article/view/918 |
| _version_ | 1811211522424176640 |
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| author | Tri Wahyudi Dava Septya Arroufu |
| author_facet | Tri Wahyudi Dava Septya Arroufu |
| author_sort | Tri Wahyudi |
| collection | DOAJ |
| description |
In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on time to their destination. Customer satisfaction is one of the most important factors in the shipping business. However, there are several obstacles that occur in the field that cause delays in the delivery of goods. Therefore, one solution that can be used to overcome this problem is to use data mining technology to predict delivery times. Using 1,000 datasets consisting of 4 Attributes, data processing will be carried out with prediction techniques using the Linear Regression algorithm. By utilizing data when the goods are taken, when the goods are on the way, until they reach the buyer, they can produce forecasts or predictions and produce several analyzes so that in the future there will be no delivery delays. Based on the RMSE (Root Mean Square Error) value which serves to generate the level value the error of the prediction results using this method and in an RMSE value of 0.370 %. It can be concluded that using the Linear Regression algorithm is proven to be accurate in predicting delivery times.
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| first_indexed | 2024-04-12T05:14:25Z |
| format | Article |
| id | doaj.art-03d95fe9249a4a8da60ad3fc224c1129 |
| institution | Directory Open Access Journal |
| issn | 2715-6087 2715-6079 |
| language | English |
| last_indexed | 2024-04-12T05:14:25Z |
| publishDate | 2022-09-01 |
| publisher | Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI) |
| record_format | Article |
| series | Journal of Applied Engineering and Technological Science |
| spelling | doaj.art-03d95fe9249a4a8da60ad3fc224c11292022-12-22T03:46:39ZengYayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)Journal of Applied Engineering and Technological Science2715-60872715-60792022-09-014110.37385/jaets.v4i1.918Implementation of Data Mining Prediction Delivery Time Using Linear Regression AlgorithmTri Wahyudi0Dava Septya Arroufu1STIKOM Cipta Karya InformatikaSTIKOM Cipta Karya Informatika In the current era of modernization, online shopping has become a habit of the people, and is closely related to freight forwarding services in charge of delivering online shopping items from the seller to the buyer. So that buyers need a fast and safe delivery service to ensure the goods sent on time to their destination. Customer satisfaction is one of the most important factors in the shipping business. However, there are several obstacles that occur in the field that cause delays in the delivery of goods. Therefore, one solution that can be used to overcome this problem is to use data mining technology to predict delivery times. Using 1,000 datasets consisting of 4 Attributes, data processing will be carried out with prediction techniques using the Linear Regression algorithm. By utilizing data when the goods are taken, when the goods are on the way, until they reach the buyer, they can produce forecasts or predictions and produce several analyzes so that in the future there will be no delivery delays. Based on the RMSE (Root Mean Square Error) value which serves to generate the level value the error of the prediction results using this method and in an RMSE value of 0.370 %. It can be concluded that using the Linear Regression algorithm is proven to be accurate in predicting delivery times. https://journal.yrpipku.com/index.php/jaets/article/view/918PredictionData MiningLinear RegressionDelivery |
| spellingShingle | Tri Wahyudi Dava Septya Arroufu Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm Journal of Applied Engineering and Technological Science Prediction Data Mining Linear Regression Delivery |
| title | Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm |
| title_full | Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm |
| title_fullStr | Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm |
| title_full_unstemmed | Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm |
| title_short | Implementation of Data Mining Prediction Delivery Time Using Linear Regression Algorithm |
| title_sort | implementation of data mining prediction delivery time using linear regression algorithm |
| topic | Prediction Data Mining Linear Regression Delivery |
| url | https://journal.yrpipku.com/index.php/jaets/article/view/918 |
| work_keys_str_mv | AT triwahyudi implementationofdataminingpredictiondeliverytimeusinglinearregressionalgorithm AT davaseptyaarroufu implementationofdataminingpredictiondeliverytimeusinglinearregressionalgorithm |