Grouping the community health center patients based on the disease characteristics using C4.5 decision tree

2017 1st International Conference on Engineering and Applied Technology

Anwar, N.^1 ; Pranolo, A.^1 ; Kurnaiwan, R.^1

Informatics Department, Universitas Ahmad Dahlan, Yogyakarta, Indonesia^1

关键词: Accuracy level;    Accuracy rate;    C4.5 algorithm;    C4.5 decision trees;    Community health centers;    Medical record;    Public health services;    Training data;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/403/1/012084/pdf
DOI  :  10.1088/1757-899X/403/1/012084

来源: IOP

【 摘 要 】

Community health centers (Puskesmas) is one of the important public health service facilities in Indonesia. Puskesmas serves many patients on performing the examination or treatment in every day. Accumulated medical record data is not utilized to generate new information or knowledge. One existed datamining techniques is the process of grouping an object with unknown label into a class. The C.45 algorithm is used to mine the patients diagnosis data available on 2015 2016. As a result, C4.5 algorithms can be applied for grouping disease. The first test using 85 training data has 78% accuracy level, while the second test of 115 training data reaches 88% accuracy rate.