PREDIKSI PENYAKIT TUBERCULOSIS PARU (TB PARU) MENGGUNAKAN METODE LEARNING VEKTOR QUANTIZATION (LVQ)

Abstract

Tuberculosis pulmonary (TB pulmonary) is a contagious disease that attacks the lungs that can spread through the air when a person active TB cough, sneeze or talk. This study aims to predict Tuberculosis pulmonary disease  using Learning Vector quantization based on data from the medical records of the health centers kamonji, Palu city. The study was conducted using 8 TB pulmonary disease risk factors which are age, gender, fever, long cough, cough, chest pain, shortness of breath, and decreased body weight. Classification is done by using 100 data consisting of 80 training data and 20 testing data. Results of the study showed that tested all the data correctly with rank of accuracy is 100%.