Planning Total Veener Production PT. XYZ

Perencanaan Jumlah Produksi (Veneer) PT. XYZ

  • Krisna Risky Putra Irawan Universitas Muhammadiyah Sidoarjo
  • Tedjo Sukmono Universitas Muhammadiyah Sidoarjo
Keywords: Forecasting Production, Support Vector Regression, Root Mean Square Error, Mean Absolute Percentage Error, Koefisien Determinasi, Peramalan Produksi

Abstract

PT. XYZ is engaged in the manufacture and sale of wood veneers. Starting from the constant occurrence of over stock, now the company must make improvements to the production forecasting process so that over stock can be avoided. It can be seen that accurate production forecasting can create conditions for an effective and efficient production system. This study aims to obtain a more accurate forecast of material requirements using the Support Vector Regression (SVR) method, which is the result of the development of a Support Vector Machine (SVM) which has good performance in predicting time series data. Application of the Support Vector Regression (SVR) method with the RBF kernel in predicting the need for veneer production using the MATLAB application, it produces the smallest error rate with a MAPE of 5%, RMSE of 4364.63 and of 0.748274147. on  67 training data and 20 testing data.

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Published
2021-07-14