Penerapan Data Mining Untuk Mempermudah Produksi Diapers Dengan Menggunakan Algoritma Regresi Linier (Studi Kasus Pada PT. Sinergi Adimitra Jaya Cibitung, Bekasi)

Tahyani Tahyani (Universitas Pelita Bangsa)
Aswan S Sunge (Universitas Pelita Bangsa)
Miftah Wangsadanureja (Universitas Pelita Bangsa)

SAINTEK
Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022

Diapers manufacturers are competing to make improvements while at the same time finding the latest formulas, it can be seen by the many brands/types of diapers on the market. Likewise, the material used by the company must import high quality materials. Material usage prediction activities are often things that must be considered so that the production and inventory processes run smoothly. So that how the calculation or estimation process can be calculated manually and with the help of the RapidMiner application or tools. Estimation methods used in Data Mining include the Linear Regression Algorithm. The test results on the SAP B material prediction, it is known that the error presentation rate using the MAPE formula is known to be 8.27% or an accuracy rate of 91.3%. Then the Linear Regression method can be used to predict material requirements quickly and efficiently. Keywords: Data Mining, Linear Regression, RapidMiner