Penerapan Logika Fuzzy Sugeno untuk Deteksi Tingkat Depresi Kerja Karyawan

Authors

  • Muhammad Daffa Universitas Islam Negeri Sumatera Utara
  • Sriani Sriani Universitas Islam Negeri Sumtera Utara

Keywords:

Depression Level, Fuzzy Logic, Body Mass Index, Patient Health Questionnaire

Abstract

The problem of depression levels among employees in a company can have a negative impact on overall performance. Therefore, the company needs additional information as a tool to detect employees' depression levels early and gain an understanding of their level of depression. Researchers applied fuzzy Sugeno to build a model for detecting employees' depression levels based on their psychological data. A dataset including variables such as weight and height, which generate Body Mass Index (BMI) values, and scores from the Patient Health Questionnaire-9 (PHQ-9), was used as input for the model. The data was then transformed into fuzzy set concepts, and fuzzy rules were built based on existing domain knowledge. The model was constructed using 60 employee respondents who had completed the questionnaire. The study utilized the Matlab application, which provides accurate results. The research findings indicate that the fuzzy Sugeno logic model is capable of detecting employees' depression levels, with results showing (63.3%) of employees experiencing mild depression, followed by (31.7%) experiencing moderate depression, and a small percentage of employees experiencing severe depression (5%).

References

Atina, A. (2019). Aplikasi Matlab pada Teknologi Pencitraan Medis. Jurnal Penelitian Fisika Dan Terapannya (JUPITER), 1(1), 28–34. https://doi.org/10.31851/jupiter.v1i1.3123

Gozali, M. I. (2020). Sistem Pengambil Keputusan Menggunakan Fuzzy Sugeno untuk Menentukan Penyakit Obesitas Anak Usia 0 sampai 16 Tahun. Jurnal Teknologi Dan Manajemen Informatika, 6(2), 90–96. https://doi.org/10.26905/jtmi.v6i2.4782

Hasanah, U., Fitri, N. L., Supardi, S., & PH, L. (2020). Depression Among College Students Due to the COVID-19 Pandemic. Jurnal Keperawatan Jiwa, 8(4), 421-424. https://doi.org/10.26714/jkj.8.4.2020.

Khairunisa, N. S., Safitri, D. R., Angelia, D., Taufan, M., & Sihaloho, E. D. (2019). Produktivitas Dan Depresi Di Indonesia: Analisis Data Indonesia Family Life Survey 014. Jurnal Ekonomi Pembangunan, 27(2), 75–84. https://doi.org/10.14203/jep.27.2.2019.75-84

Najamuddin, M., Miharja, D., & Adhkar, S. (2022). Implementasi Chatbot Deteksi Depresi Dini Pada Mahasiswa dengan PHQ-9 (Patient Health Questionnaire) menggunakan NLP (Natural Language Processing). Prosiding SAINTEK: Sains Dan Teknologi, 1(1), 103–108.

Pratiwi, T. K., & Astuti, Y. P. (2020). Penentuan Level Depresi Mahasiswa Tingkat Akhir Menggunakan Sistem Inferensi Fuzzy dengan Metode Sugeno. MATHunesa: Jurnal Ilmiah Matematika, 8(3), 269–273. https://doi.org/10.26740/mathunesa.v8n3.p269-273

Putri, A. D. (2017). Fuzzy Logic Untuk Menentukan Lokasi Kios Terbaik Di Kepri Mall Dengan Menggunakan Metode Sugeno. Edik Informatika, 3(1), 49–59. https://doi.org/10.22202/ei.2016.v3i1.1517

Rasyid, M. F. Z. (2021). Pengaruh Asupan Kalsium Terhadap Indeks Masa Tubuh (IMT). Jurnal Medika Hutama, 2(4), 1094–1097.

Rostampour, N., Naderi, M., Rostampour, N., & Safavi, P. (2022). The relationship between body mass index and depression, anxiety, body image, and eating attitudes in adolescents in Iran. Advanced Biomedical Research, 11(1), 51–55. https://doi.org/10.4103/abr.abr_259_20

Septiani, D., Enri, U., & Sulistiyowati, N. (2021). Diagnosa Tingkat Depresi Mahasiswa Selama Masa Pandemi Covid-19 Menggunakan Algoritma Random Forest. STRING (Satuan Tulisan Riset Dan Inovasi Teknologi), 6(2), 149–157. https://doi.org/10.30998/string.v6i2.10361

Sriani, S. (2019). Pemanfaatan Sistem Pengendali Water Level Control Untuk Budidaya Ikan Gurame Pada Kolam Terpal Menggunakan Logika Fuzzy Berbasis Mikrokontroler. Elkawnie, 5(1), 47–57. https://doi.org/10.22373/ekw.v5i1.3766

Sugihartono, P. P. P., Hidayat, N., & Tibyani, T. (2020). Implementasi Metode Fuzzy Tsukamoto Untuk Deteksi Dini Tingkat Depresi Mahasiswa Yang Sedang Menempuh Skripsi (Studi Kasus: Fakultas Ilmu Komputer Universitas Brawijaya). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 4(10), 3432–3438.

Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 3 Juli 2023

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Published

2023-07-30

How to Cite

Daffa, M., & Sriani, S. (2023). Penerapan Logika Fuzzy Sugeno untuk Deteksi Tingkat Depresi Kerja Karyawan. Jurnal Teknologi Sistem Informasi Dan Aplikasi, 6(3), 484–493. Retrieved from https://openjournal.unpam.ac.id/index.php/JTSI/article/view/32020

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Vol. 6 No. 3 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi

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Copyright (c) 2023 Muhammad Daffa, Sriani Sriani

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