Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio
TB. Wijaya Bangunan is a business entity that has weaknesses in managing inventories. This study aims to help TB. Wijaya Bangunan in managing inventory based on existing data reduce the difference between the number of incoming goods and the number of outgoing goods. The methods used are data collec...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Islam Negeri Sunan Kalijaga Yogyakarta
2021-05-01
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| Series: | JISKA (Jurnal Informatika Sunan Kalijaga) |
| Online Access: | http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2095 |
| _version_ | 1797709457093820416 |
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| author | Natcha Kwintarini Suparman Budi Arif Dermawan Tesa Nur Padilah |
| author_facet | Natcha Kwintarini Suparman Budi Arif Dermawan Tesa Nur Padilah |
| author_sort | Natcha Kwintarini Suparman |
| collection | DOAJ |
| description | TB. Wijaya Bangunan is a business entity that has weaknesses in managing inventories. This study aims to help TB. Wijaya Bangunan in managing inventory based on existing data reduce the difference between the number of incoming goods and the number of outgoing goods. The methods used are data collection, data preparation, data selection, preprocessing, data transformation, distance calculation, calculation of predictions, evaluation, and display of prediction results using a Shiny framework. This study uses the Time Series KNN Regression algorithm to predict the number of outgoing goods based on time series data with existing data. The most predicted results came out in the 9th week period as much as 22.40%. Based on the process that has been done, it can be concluded that the evaluation value of Root Mean Square Error (RMSE) is at least 3.55, which means it has the best predictive accuracy results. |
| first_indexed | 2024-03-12T06:37:54Z |
| format | Article |
| id | doaj.art-2b5fb1858a854f55a6e1f1e7950786ed |
| institution | Directory Open Access Journal |
| issn | 2527-5836 2528-0074 |
| language | English |
| last_indexed | 2024-03-12T06:37:54Z |
| publishDate | 2021-05-01 |
| publisher | Universitas Islam Negeri Sunan Kalijaga Yogyakarta |
| record_format | Article |
| series | JISKA (Jurnal Informatika Sunan Kalijaga) |
| spelling | doaj.art-2b5fb1858a854f55a6e1f1e7950786ed2023-09-03T01:11:56ZengUniversitas Islam Negeri Sunan Kalijaga YogyakartaJISKA (Jurnal Informatika Sunan Kalijaga)2527-58362528-00742021-05-016210.14421/jiska.2021.6.2.90-97Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudioNatcha Kwintarini Suparman0Budi Arif Dermawan1Tesa Nur Padilah2Universitas Singaperbangsa KarawangUniversitas Singaperbangsa KarawangUniversitas Singaperbangsa KarawangTB. Wijaya Bangunan is a business entity that has weaknesses in managing inventories. This study aims to help TB. Wijaya Bangunan in managing inventory based on existing data reduce the difference between the number of incoming goods and the number of outgoing goods. The methods used are data collection, data preparation, data selection, preprocessing, data transformation, distance calculation, calculation of predictions, evaluation, and display of prediction results using a Shiny framework. This study uses the Time Series KNN Regression algorithm to predict the number of outgoing goods based on time series data with existing data. The most predicted results came out in the 9th week period as much as 22.40%. Based on the process that has been done, it can be concluded that the evaluation value of Root Mean Square Error (RMSE) is at least 3.55, which means it has the best predictive accuracy results.http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2095 |
| spellingShingle | Natcha Kwintarini Suparman Budi Arif Dermawan Tesa Nur Padilah Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio JISKA (Jurnal Informatika Sunan Kalijaga) |
| title | Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio |
| title_full | Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio |
| title_fullStr | Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio |
| title_full_unstemmed | Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio |
| title_short | Prediksi Barang Keluar TB. Wijaya Bangunan Menggunakan Algoritma KNN Regression dengan RStudio |
| title_sort | prediksi barang keluar tb wijaya bangunan menggunakan algoritma knn regression dengan rstudio |
| url | http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2095 |
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