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All Journal Nursing News : Jurnal Ilmiah Keperawatan Journal of Agro Complex JURNAL MANAJEMEN PENDIDIKAN ISLAM AL-IDARAH Jurnal Computer Science and Information Technology (CoSciTech) An-Nawa : Jurnal Studi Islam Analit: Analytical and Environmental Chemistry At Tasyri'i Jurnal Prodi Perbankan Syariah Jurnal Ilmiah Research Student El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teras Pengabdian Masyarakat
Miftahur Rahman
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Religion Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences

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Optimasi Metode Certainty Factor Menggunakan Rank Order Centroid Pada Sistem Pakar Pendeteksi Turnover Intention Berbasis WEB Muhammad Maulana Akbar; Moh. Dasuki; Miftahur Rahman
Computer Science and Information Technology Vol 6 No 2 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i2.9869

Abstract

Turnover intention, or the tendency of employees to resign, poses a significant challenge for companies—especially when dealing with Generation Z, who tend to have lower job commitment and are more likely to switch jobs. This study aims to develop a web-based expert system to detect the level of employee turnover intention by integrating the Certainty Factor (CF) and Rank Order Centroid (ROC) methods. The CF method is used to handle uncertainty in questionnaire assessments, while ROC is implemented to optimize the weights among aspects, namely Thinking of Quitting, Intention to Search for Alternatives, and Intention to Quit. The system is built based on 36 questionnaire statements and tested on 34 respondents. The results show that the system provides more proportional and realistic interpretations compared to the non-optimized approach. Accuracy testing indicates that 27 out of 34 system results match manual assessments, yielding an accuracy rate of 79.41%. These findings suggest that the system performs reliably and can serve as a practical tool for the early detection of turnover intention in the workplace.
Co-Authors Achmad Abdul Fatah Adi Sucipto, Adi Agung Abadi Kiswandono Ananda Galang Wangsa Ardiyani, Vita Maryah Astuti B Erdiansyah Putra Budi Adi Kristanto Daffa Agung Nugroho Dian Pratama Dwi Aisah Saraswati Fadlun Herlambang Satria Wijaya Ida Faridah Izzah Tujannah Karno Karno Mochammad Rifki Ulil Albaab Moh. Dasuki Moh. Ferdi Ardiansyah Muhaimin Muhammad Maulana Akbar Ni Luh Gede Ratna Juliasih Purna Pirdaus Putri Adelia Khairunnisa Rachmadani Anggowo Rizky Rina Wati Syifa Al Murtadho Tanto Hariyanto Tegar Alam Qushoyyi