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All Journal Maeswara: Jurnal Riset Ilmu Manajemen dan Kewirausahaan
Debora Rifiani Gosita
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Analisa Pengaruh Penggunaan Teknologi Dalam Manajemen Evaluasi Kinerja Debora Rifiani Gosita; Sri Sundari; Marisi Pakpahan
Maeswara : Jurnal Riset Ilmu Manajemen dan Kewirausahaan Vol. 2 No. 2 (2024): APRIL : Maeswara
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/maeswara.v2i2.725

Abstract

Recent developments in information and communication technology such as artificial intelligence (AI) provide new opportunities to increase the efficiency and accuracy of performance assessment. The impact of the COVID-19 pandemic and the shift to a remote work model has created a need for technology solutions to unify and transmit the performance of employees working from multiple locations. The use of technology in performance management evaluations may raise concerns regarding data security and privacy, inconvenience or resistance to employees or stakeholders. Not all employees or managers have the same level of skill and understanding of the technology being implemented and it requires a high initial investment in maintenance and upgrades. This article provides an understanding of how technology can be applied in management performance evaluation and its benefits in increasing efficiency, objectivity and accuracy in employee assessment as well as providing recommendations for innovation and changes in the use of technology in management performance evaluation. The methodology used is a qualitative method by collecting data from various information sources. Some of the positive impacts of implementing technology in performance evaluation management are increased efficiency and productivity, real-time feedback, increased objectivity and fairness, more accurate and measurable performance monitoring. The technologies that can be used are Go Talent, Feedback and Recognition Systems, Analytics Technology, Application-Based Performance Evaluation Systems, Use of AI for Objective Evaluation and Chabots for Feedback.
Co-Authors Marisi Pakpahan Sundari, Sri