Published: 2024-10-01
Implementasi Sistem Pendukung Keputusan Pemilihan Tenaga Kesehatan Terbaik Menggunakan Metode Weighted Product (WP)
DOI: 10.35870/jtik.v8i4.2614
Abstract
This research aims to develop a web-based decision support system (DSS) for selecting the best healthcare professionals using the Weighted Product (WP) method. The system is designed to assist hospital institutions in determining the best healthcare professionals based on the criteria set by the Minister of Health Regulation of the Republic of Indonesia Number 23 of 2016. The research was conducted at CV Sumber Solusi Bersama, focusing on the development of a Hospital Management System. The WP method was chosen for its ability to handle complex multi-criteria decision-making. The results of the research indicate that the developed system can improve efficiency and accuracy in the process of selecting the best healthcare professionals, thereby enhancing the quality of healthcare services in hospitals.
Keywords
Decision Support System; Healthcare Personnel; Assessment; Weighted Product; Website; Recommendation System; Ranking; Healthcare Workers; DSS; PHP
Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 8 No. 4 (2024)
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Section: Computer & Communication Science
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Published: 2024-10-01
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License: CC BY 4.0
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Copyright: © 2024 Authors
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DOI: 10.35870/jtik.v8i4.2614
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Muhammad Nur Ikhsanuddin, , Universitas Duta Bangsa Surakarta
Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Duta Bangsa Surakarta, Kota Surakarta, Provinsi Jawa Tengah, Indonesia.
Agustina Srirahayu, , Universitas Duta Bangsa Surakarta
Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Duta Bangsa Surakarta, Kota Surakarta, Provinsi Jawa Tengah, Indonesia.
Nibras Faiq Muhammad, , Universitas Duta Bangsa Surakarta
Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Duta Bangsa Surakarta, Kota Surakarta, Provinsi Jawa Tengah, Indonesia.
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Napila, A., & Hidayat, A. (2023). Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Weight Product (Studi Kasus: Klinik Sehat Serpong). Journal of Research and Publication Innovation, 1(3), 888-893.
-
Santika, R. R., Kamila, A., Abdillah, M. I., & Hansen, S. (2020). Penerapan Metode Profile Matching Dalam Sistem Penunjang Keputusan Pemilihan Karyawan Terbaik Pada Lembaga Penyiaran Publik Televisi Republik Indonesia. Jurnal Inovtek Polbeng Seri Informatika, 5(1), 68-82. DOI: https://doi.org/10.35314/isi.v5i1.1311.
-
Perwira, Y. (2019). Penentuan Peringkat Pelanggan Terbaik dengan Metode Weighted Product (Studi Kasus di PT. Asia Raya Foundry): Penentuan Peringkat Pelanggan Terbaik dengan Metode Weighted Product (Studi Kasus di PT. Asia Raya Foundry). Jurnal Mantik, 3(1), 138-147.
-
Sari, R. P., & Novitasari, L. (2022). Sistem Penentuan Kelayakan Kredit Pemilikan Rumah Non-Subsidi Menggunakan Metode Weight Product. J. Rekayasa Teknol. Inf. JURTI, 6, 18-25.
-
Silmina, E. P., & Hardiani, T. (2022). Sistem Pendukung Keputusan Pemilihan Menu Makan untuk Balita Menggunakan Metode Weight Product. Jurnal Inovtek Polbeng Seri Informatika, 7(2), 297-307. DOI: https://doi.org/10.35314/isi.v7i2.2647.
-
Firdaus, A., & Priyanggodo, D. Y. (2020). Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Weighted Product. JIKA (Jurnal Informatika), 4(3), 94-96. DOI: http://dx.doi.org/10.31000/jika.v4i3.2982.
-
Fridayanthie, E. W., Khoirurrizky, N., & Santoso, T. (2020). Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Weighted Product. Paradig.-J. Komput. dan Inform, 22(1), 41-46.
-
Samsir, S., Ambiyar, A., Verawardina, U., Edi, F., & Watrianthos, R. (2021). Analisis Sentimen Pembelajaran Daring Pada Twitter di Masa Pandemi COVID-19 Menggunakan Metode Naïve Bayes. Jurnal Media Informatika Budidarma, 5(1), 157-163.
-
Pasaribu, A. F. O., & Nuroji, N. (2023). Sistem Pendukung Keputusan Penentuan Pelanggan Terbaik Menggunakan Profile Matching. Journal of Data Science and Information Systems, 1(1), 24-31.
-
Telaumbanua, R. F. (2020). Peran Tenaga Kesehatan dalam Melaksanakan Pelayanan Kesehatan WBP Rutan. Jurnal Ilmiah Kesehatan Sandi Husada, 9(1), 205-212. DOI: 10.35816/jiskh.v11i1.247.
-
Zamani, A., Rokhmatun, P. N., Maesaroh, S., Widiyanto, A., & Atmojo, J. T. (2023). Peningkatan Motivasi Kerja Tenaga Kesehatan dengan Administrasi Rumah Sakit: Meta-Analisis. Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal, 13(2), 443-452. DOI: https://doi.org/10.32583/pskm.v13i2.910.
-
Aroral, H. K. (2021). Waterfall process operations in the fast-paced world: project management exploratory analysis. International Journal of Applied Business and Management Studies, 6(1), 91-99.
-
Srirahayu, A., & Suryani, F. (2023). Prototype Sistem Informasi Diagnosis Cabai Berbasis Android. In Prosiding Seminar Nasional Amikom Surakarta (pp. 219-225).
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