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...

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Bibliographic Details
Main Authors: Natcha Kwintarini Suparman, Budi Arif Dermawan, Tesa Nur Padilah
Format: Article
Language:English
Published: Universitas Islam Negeri Sunan Kalijaga Yogyakarta 2021-05-01
Series:JISKA (Jurnal Informatika Sunan Kalijaga)
Online Access:http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2095
Description
Summary: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.
ISSN:2527-5836
2528-0074