Application of Predictions for the Total Productivity of Competency Certificates Electrical Engineering Staff at PT. Eleska Iatki Using Artificial Neural Network Backpropagation Algorithm

Rika Mulyati, Nur Ichsan Utama, Adi Raharjo, Sunaryo Marwa, Nusyirwan

Abstract: The productivity value is a critical performance assessment criterion for Competency Certification Institutes LSK for electrical engineering personnel in Indonesia, overseen by the Directorate General of Electricity DJK. This study aims to predict the productivity of competency certificates issued by PT Eleska Iatki using an Artificial Neural Network ANN with the Backpropagation algorithm. Accurate predictions are essential for developing business strategies and maintaining high performance amidst competitive pressures. Data from 2018 to 2022, consisting of certificate issuance records, were utilized. The studys methodology included data collection, preprocessing, prediction modeling, and accuracy testing, resulting in a prediction accuracy of 91.3 with a Mean Absolute Percentage Error MAPE of 9.7.

Keywords: Prediction, Competency Certificate, Artificial Neural Network, Backpropagation Algorithm, Mean Absolute Percentage Error

How to Cite?: Rika Mulyati, Nur Ichsan Utama, Adi Raharjo, Sunaryo Marwa, Nusyirwan, "Application of Predictions for the Total Productivity of Competency Certificates Electrical Engineering Staff at PT. Eleska Iatki Using Artificial Neural Network Backpropagation Algorithm", Volume 13 Issue 6, June 2024, International Journal of Science and Research (IJSR), Pages: 552-557, https://www.ijsr.net/getabstract.php?paperid=SR24606084908, DOI: https://dx.doi.org/10.21275/SR24606084908