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Journal : jupiter

Klasifikasi Persediaan Stok Darah Menggunakan Algoritma K-NN, Decision Tree, dan JST Backpropagation Rijal Fauzan, Yulis; Fajarendra, Yusril Iza; Ridha , M Noor Tasiur; 'Uyun, Shofwatul
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13755935

Abstract

The demand for blood is critical for various purposes, such as surgeries, transplants, cancer treatments, dialysis, and disaster victims. The availability of blood at the Blood Transfusion Unit (UTD) of the Indonesian Red Cross (PMI) is crucial, as a shortage of stock can endanger patients' lives. Therefore, this study aims to evaluate the condition of blood stock to determine whether it is safe or insufficient. This research focuses on comparing blood stock classification at PMI Kota Yogyakarta using three algorithms: K-Nearest Neighbor, Decision Tree, and Artificial Neural Network (Backpropagation). The study objects consist of 216 blood stock data point. Testing is conducted using the K-Fold Cross Validation method with a k value of 8 on 216 data points. The research results show that the K-Nearest Neighbors (KNN) algorithm achieves an Accuracy of 85.18%, Recall of 85.03%, Precision of 89.25%, F1-Score of 87.09%, and Specificity of 84.39%. The Decision Tree algorithm achieves an Accuracy of 84.72%, Recall of 88.18%, Precision of 86.15%, F1-Score of 87.15%, and Specificity of 78.08%. The Artificial Neural Network (Backpropagation) algorithm shows the best performance with an Accuracy of 93.05%, Recall of 96.06%, Precision of 92.42%, F1-Score of 94.20%, and Specificity of 89.35%. Thus, it can be concluded that the Artificial Neural Network (Backpropagation) algorithm outperforms the other algorithms in classifying blood stock availability.  Keywords—PMI, Blood, Classification, K-Nearest Neighbor, Decision Tree, Backpropagation
Co-Authors Abdullah, Mohd. Fikri Azli bin Agung Nur Hidayat Ahmad Mustafid Ahmad Subhan Yazid Akbar, Riolandi Akhmad Imam Fahrizal Alfarizi, Naufal Faiz Arif Riyandi Arromdoni, Bad’ul Hilmi Awaliyah, Dien Fitri Bambang Sugiantoro Danang Aji Bimantoro Daru Prasetyawan Diniati Ruaika Dony Fahrudy Dori Gusti Alex Candra Eka Sulistiyowati Eka Sulistyowati Eka Sulistyowati, Eka Elvanisa Ayu Muhsina Elvanisa Ayu Muhsina, Elvanisa Ayu Endra Yuliawan Fahrudy, Dony Fajarendra, Yusril Iza Fauzi, Muhammad Dzulfikar Hardandrito, Awan Gumilang Helmiyah, Siti Heni Hapsari Iin Intan Uljanah Imam Riadi Istianto, Yudi Iza Fajarendra, Yusril Khuluq, Nur Fikri Lina Choridah Madikhatun, Yuni Mardlian, M. Sa’id Abdurrohman Kunta Maria Ulfah Siregar Mufafaq, Naufal Hafizh MUHAMMAD ABDUL GHOFUR Muhammad Akid Musyafa Muhammad Anshari, Muhammad Muhammad Edi Iswanto Muhammad Fadzlur Rahman Muhammad Rifqi Ma'arif Muhammad Taufiq Nuruzzaman Murdifin, Murdifin Mustafid, Ahmad Muzhaffar, Muh Naufal Nuri Guntur Perdana Nurochman Nurochman Nuruzzaman, Muhammad Taufiq Pratiwi, Millati Qonitat, Ihda Imroatun Qorry Aina Fitroh Rahardyan, Seto Rebeccah Ndungi Ridha , M Noor Tasiur Rijal Fauzan, Yulis Riwanto, Yudha Rizal Fauzan, Yulis Rosalia Susilowati Rosalin, Rizqi Praimadi Saiful Machbub Mutaqin Sanora, Fiki Sari, Luky Vianika Sherly Andini Sri Hartati subanar subanar Sucinta, Hanny Handayani Toni Efendi Tundo, Tundo Ulfah, Aniq Noviciate Yudha Riwanto Yulis Rijal Fauzan Yuni Madikhatun Yuni Madikhatun