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All Journal JPTK: Jurnal Pendidikan Teknologi dan Kejuruan snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Syntax Jurnal Informatika Jurnal Pseudocode INTEGER: Journal of Information Technology Sebatik Jurnal Basicedu JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurnal Pendidikan dan Teknologi Indonesia Jurnal Media Informatika Asian Journal of Community Services (AJCS) Jurnal Basicedu Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Jurnal Informatika: Jurnal Pengembangan IT Jurnal Multidisiplin Indonesia
Setiani, Novi
Informatika, Universitas Islam Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : INTEGER: Journal of Information Technology

 1 
Perbandingan LLM pada OpenAI untuk Mengevaluasi Kinerja Pegawai di PT Javan Cipta Solusi Setiani, Novi
INTEGER: Journal of Information Technology Vol 11, No 1 (2026): Maret
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2026.v11i1.8169

Abstract

. Evaluating the performance of the best employees in a company is a common problem faced by the human resources division. Assessing subjectively and comprehensively is a challenge that must be overcome in building sustainable business growth. For organizations that are already able to manage employee assignment data in a structured and systematic form, this can be done by processing quantitative data obtained from the task management system. In this study, a large language model-based approach is proposed to identify the best employees based on assignment data for one year. A comparison was made of six versions of LLM on OpenAI to measure employee performance based on a predetermined prompting design. As a result, 50% of respondents considered that the criteria proposed by GPT4o-mini were more appropriate to their needs, and 60% of respondents considered that the employee ranking results produced by GPT-4 were more relevant to the reality.
Co-Authors Aldhiyatika Amwin Chaerulisma, Hanuga Fathur Dadan Nugraha Dani, Erwan Deka Dwinavinta Candra Nugraha Dimas Setyawan Ramadhansyah Dimastyo Muhaimin Arifin Divia, Helga Aurellia Dwi Abdul Rahman Fakhrii, Rifaldi Fathul Wahid Fauzan Awanda Alviansyah Fauzi, Fikri Achmad Febrian, Fajar Fionna Saphira Farhani Fitriati , Siti Hanson P. Putro Husein Arif Budiman Ike Agustina Irena Yolanita Maureen Izhar , Izhar Khairunnisa, Adinda Khansa Mahendri, Yusril Makhfuzi Fahmi Muhammad Zaki Al Ghifari Nihayah, Maryama Nugraha, Giri Nur W. Rahayu Palsa, Al Fatih Berlian Paputungan, Irving Vitra Prasetyo, Gilang Aries Pratiwi, Ratri Rahma, Indah Kartika Raisha Amini Dinda Salechah Rizqi Kartika Safitri Rosyidah. S, Ghaniyya . Sabika Amalina Salsabilla, Selfira Setiaji, Hari Siraj, Muhammad Rizki sri mulyati Sri Yunianita Tatik Tatik, Tatik Teduh Dirgahayu Vebri Satriadi Wulandari, Meida Arriwani Yudhistira Adinugraha Hutabarat Yuningsih, Epa Zainudin Zukhri Zumrotun Naimah