Application of blood donor routine detector using K-Nearest neighbors

2nd International Conference on Natural Resources and Life Sciences

生态环境科学

Nurdiansyah, Y.^1 ; Pandunata, P.^1 ; Prasetyo, N.D.^1 ; Trihartono, A.^2 ; Putrianti, F.G.^3 ; Wijayanto, F.^4

Faculty of Computer Science, Universitas Jember (UNEJ), Jl. Kalimantan 37, Jember

68121, Indonesia^1

Center for Research in Social Sciences and Humanities (C-RiSSH), Universitas Jember (UNEJ), Jl. Kalimantan 37, Jember

68121, Indonesia^2

University of Sarjanawiyata Tamansiswa, Jl. Kusumanegara No.157, Yogyakarta

55165, Indonesia^3

Institute for Computing and Information Science, Radbound University, Comenisulaan 4, Nijmegen

6525 HP, Netherlands^4

关键词: Indonesian Red Cross;    K-nearest neighbors;    K-nearest neighbors method;    Routine detections;    SIMPLE algorithm;    Sms gateways;    Training data;    Waterfall model;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/293/1/012042/pdf
DOI  :  10.1088/1755-1315/293/1/012042

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The application of blood donor routine detection using the K-nearest Neighbors method at UTD PMI (Unit Transfusi Darah, Palang Merah Indonesia, Indonesian Red Cross, Hereafter PMI) is a system that aims to provide the class status of the donors aimed at facilitating the employee in selecting the right donor to be recontacted. The K-Nearest Neighbors method is used to calculate the distance of the test data with the training data. The K-nearest Neighbors method is chosen because it has a simple algorithm, works based on the shortest distance from the test data sample to the training data sample to determine the distance. The creation of this system is built by adapting the waterfall model. The objective is that the system is able to implement the K-nearest Neighbors method to help determine the class status of the donors and that the system can send SMS gateway to the donors that donor information can be publicly published. The test calculation uses full train full set testing on all training data and the result of K5=84 %, K7=88 %, K9=87 %, K11=82 %, K13=77 %, K15=75 %. The highest result is on the K7.