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All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer)
Aleksander Nainggolan
Universitas Prima Indonesia
Computer Science & IT

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PENENTUAN KELAYAKAN PROMOSI PEGAWAI MENGGUNAKAN ALGORITMA RANDOM FOREST CLASSIFIER DAN XGBOOST CLASSIFIER Elvis Sastra Ompusunggu; Aleksander Nainggolan; Meri Kristina Sihombing
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.949

Abstract

Perkasa Internusa Mandiri is a company engaged in the field of Property Management. One of the problems employees to become permanent employees is that it still needs to be more effectives; this raises doubts in decision-making, allowing mistakes to occur. In this context, to solve problems at PT. Perkasa Intenusa Mandiri uses a classification algorithm to provide a more objective and transparent solution. This study aims to apply a data-based approach using the Random Forest Classifier and XGBoost Classifier algorithms to assess the feasibility of promoting contract employees to permanent employees. In this study, the Random Forest classification algorithm and the XGBoost Classifier have also produced good accuracy values, whereas the Random Forest has an accuracy of 86.8%. In comparison, the XGBoost Classifier has an accuracy of 83.5%. Both models have good performance (because the accuracy is above 80%) and can be implemented in real-world cases in the future.
Co-Authors Elvis Sastra Ompusunggu Meri Kristina Sihombing