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All Journal Sagita Academia Journal
M. Kana Putra
Program Studi Teknik Informatika Fakultas Teknik Universitas Jabal Ghafur
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media

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PENERAPAN METODE PROFILE MATCHING PADA SISTEM PENDUKUNG KEPUTUSAN KELAYAKAN PASIEN UNTUK SUNTIK VAKSIN COVID-19 BERBASIS WEB M. Kana Putra; Junaidi Salat
Sagita Academia Journal Vol. 2 No. 2 (2024): Sagita Academia Journal
Publisher : Yayasan Sagita Akademia Maju

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61579/sagita.v2i2.62

Abstract

The handling of the COVID-19 pandemic is not only carried out in terms of implementing health protocols but also interventions with vaccinations as part of efforts to prevent and control COVID-19. In implementing the current vaccine, there are still many errors in administering vaccines to people who are not eligible or should not be vaccinated, this is due to the ignorance of the people who will receive the vaccine regarding the criteria that need to be considered before receiving the COVID-19 vaccine. So that this ignorance has resulted in victims, where vaccine recipients have fainted, some have even resulted in death. The purpose of this study is to apply the profile matching method to a decision support system for patient eligibility to inject the Covid-19 vaccine. In this study the system was built using a web-based programming language, and using MySQL to accommodate data. As for the process of evaluating the eligibility of patients given vaccine injections using the profile-matching method. The results of this study can help simplify and speed up the due diligence process to determine the administration of the COVID-19 vaccine injection to patients/the public, and can make it easier for the public to access information regarding their eligibility to be given the Covid-19 vaccine, as well as provide a sense of security in receiving the Covid vaccine -19.
Co-Authors Junaidi Salat