Employee Performance Assessment Model in Survey Service Companies Using Analytical Hierarchy Process and Naive Bayes

Abstract

Assessment of the performance of employees of a survey service company produces a final score that is not in accordance with the company's transformation strategy in responding to external challenges and demands. The variable assessment process still uses 180 Degree Feedback which is one-way from superiors to employees. This makes the company's learning and growth activities, especially in the human resources department, not occur. Therefore, companies should improve the assessment model to become a tool for acquiring highly qualified performing employees. This study contributes to obtain a more comprehensive employee performance assessment model proposal and evaluate the model so that it can be implemented. The research limitation lies in the use of data, namely contract employees with the position of Project Manager. This study uses the Analytical Hierarchy Process and Naïve Bayes methods to obtain variable weights. Based on the results of the analysis, it was found that SOE (State Owned Enterprises) AKHLAK was a new variable. The classification of the assessment variables is divided into Performance and Behavioral aspects based on the Minister of SOE Regulation. Changes that occur include formulas, mechanisms, and rating scales. The results of the verification and validation show that the model is in accordance with the design so that it can be implemented. Model trials with 360 DF show that PM's final score has a good chance of being assessed as a full-time employee. This valuation model can change along with company policies in responding to internal and external changes.