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All Journal Fortech : Journal of Information Technology
Besse Eka Mardiana Putri
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Computer Science & IT

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IMPLEMENTASI DATA MINING METODE NAÏVE BAYES UNTUK PREDIKSI KELAYAKAN PENDONOR DI UDD PMI KOTA JAMBI Novhirtamely Kahar; Besse Eka Mardiana Putri
FORTECH (Journal of Information Technology) Vol 10 No 1 (2026): Fortech (Journal Of Information Technology)
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/a0f3eb75

Abstract

The Blood Donation Unit (UDD) of PMI Kota Jambi plays an important role in maintaining the availability of safe and eligible blood supplies. One of the challenges faced is that the determination of donor eligibility is still carried out manually and relies heavily on medical staff examinations, which may lead to inefficiency and delays in service. Therefore, a predictive model is needed to assist in determining donor eligibility more quickly and objectively.This study aims to apply data mining techniques using the Naïve Bayes algorithm to predict the eligibility of blood donors at UDD PMI Kota Jambi. The data used consist of historical donor records, including attributes such as age, gender, body weight, blood pressure, hemoglobin level, and donor history.
Co-Authors Novhirtamely Kahar